基于协同多相注入的二氧化碳提高采收率与封存技术研究进展

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Background Strongly water-sensitive reservoirs with high clay content face challenges in conventional development due to clay swelling and impeded seepage. CO2 injection shows potential for enhanced oil recovery (EOR) and carbon sequestration; however, the role of clay minerals in regulating CO2-induced asphaltene deposition and sequestration remains unclear. Methodology We conducted experiments on clay-oil interactions, nuclear magnetic resonance (NMR), measurements of crude oil properties, and long core water flooding tests to evaluate deposition, reservoir damage, and CO2 sequestration. Conclusions/Significance Results demonstrate that clay minerals significantly promote CO2-induced asphaltene deposition, with the deposition amount in clay-containing crude oil increasing by 37% compared to clay-free systems. The interfacial tension (IFT) between crude oil and CO2 decreases from 15.68 to 12.53 mN/m at 10 MPa with increasing clay content, while crude oil viscosity reduces by up to 43.58% when CO2 injection exceeds 30 mol%. Microscale NMR analysis confirms that clay-asphaltene aggregates preferentially block large pores, reducing reservoir heterogeneity and enhancing CO2 sequestration in medium/small pores. Macroscale long-core experiments highlight the significance of high clay mineral content for geological sequestration, showing that the CO2 sequestration rate increases from 43.15% to 48.21% as clay content rises from 8.35% to 29.92%. Although deposition slightly impairs permeability, it drives CO2 into medium/small pores, thereby achieving a balance between oil recovery efficiency and long-term storage stability.

The integrated injection of low-salinity water (LSW) and carbon dioxide (CO2) into the water-alternating-gas (WAG) process offers advantages, primarily increasing oil recovery and reducing operating costs. However, CO2 has challenges in sweep efficiency due to significant differences in density and viscosity compared with oil. While LSW and dimethyl ether (DME) have shown promise in improving recovery through wettability alteration and reducing minimum miscible pressure, interfacial tension (IFT), and CO2 mobility, their synergistic integration with CO2-WAG remains poorly understood. Existing DME-based enhanced oil recovery (EOR) studies have not explored low-salinity water injection as a cost-effective alternative to mitigate high DME operating costs. This study introduces the CO2/DME-LSWAG method, systematically evaluating the effect of DME concentrations (0%, 10%, 25%) and LSWs (seawater, twice-diluted seawater, ten-times-diluted seawater) on sweep and displacement efficiencies, oil recovery, and CO2 storage in a 2D cross-sectional carbonate reservoir model. Results showed that DME dramatically reduces IFT (67% and 95% at 10% and 25% DME solvent, respectively) while salinity effects are relatively small. Compared with CO2-LSWAG, the oil recovery factor improved by 5.2–13.1% depending on DME concentration and water salinity, with DME performance maximized at higher salinity water. CO2 storage efficiency showed opposing trends. Structural trapping decreased, while solubility trapping increased with lower salinity. The sensitivity analysis identified DME concentration as the dominant factor for CO2 storage. The composition modeling and simulation of the CO2/DME-LSWAG process provide critical engineering guidance for the design of future EOR and CO2 storage projects that utilize DME in carbonate reservoirs.

How to economically and effectively mobilize remaining oil and achieve carbon sequestration after water flooding in low-permeability, high-water-cut reservoirs is an urgent challenge. This study, focusing on Block Y of the Daqing Oilfield, employs numerical simulation to systematically reveal the synergistic influencing mechanisms of CO2 flooding and geological storage. A three-dimensional compositional model characterizing this reservoir was constructed, with a focus on analyzing the controlling effects of key geological (depth, heterogeneity, physical properties) and engineering (gas injection rate, gas injection volume, bottom-hole flowing pressure) parameters on the displacement and storage processes. Simulation results indicate that the low-permeability characteristics of Block Y effectively suppress gas channeling, enabling a CO2 flooding enhanced oil recovery (EOR) increment of 15.65%. Increasing reservoir depth significantly improves both oil recovery and storage efficiency by improving the mobility ratio and enhancing gravity segregation. Parameter optimization is key to achieving synergistic benefits: the optimal gas injection rate is 700–900 m3/d, the economically reasonable gas injection volume is 0.4–0.5 PV, and the optimal bottom-hole flowing pressure is 9–10 MPa. This study confirms that for Block Y and similar high-water-cut, low-permeability reservoirs, CO2 flooding is a highly promising replacement technology; through optimized design, it can simultaneously achieve significant crude oil production increase and efficient CO2 storage.

CO2 injection has gained popularity in the petroleum industry as a dual-purpose method for enhanced oil recovery (EOR) and long-term carbon sequestration. However, assessing the performance of CO2 EOR and its storage potential across large-scale fields is a complex task, primarily due to the heterogeneous geological characteristics of reservoirs and the dynamic behavior of injected CO2. Traditional methods for evaluating CO2 injection often rely on manual interpretations or computationally expensive reservoir simulations, both of which can be biased, time-intensive, and less effective for field-wide analyses involving extensive datasets. In this study, a data mining-driven methodology was developed and applied to one of the most prominent CO2 injection projects in the world. More than 2,000 wells with decades-long production histories were analyzed using advanced statistical and geostatistical approaches, including spatial and temporal normalization of production data. By correlating key production metrics with geological features inferred from the data, fracture-dominated and matrix-dominated regions within the field were identified. The analysis further highlighted zones with differing CO2 injection efficiency and oil displacement behavior, providing a comprehensive understanding of reservoir performance in terms of oil recovery and CO2 sequestration. A critical aspect of the methodology involved combining multiple production metrics—such as gas-oil ratio (GOR), water cut, time to peak production, and CO2 breakthrough patterns—using z-score-based normalization across both spatial and temporal domains. This approach enabled localized trend interpretation while maintaining consistency with physical reservoir behavior. Zones where CO2 injection was successful in both enhancing oil recovery and sequestering carbon were differentiated from areas where CO2 rapidly broke through without effective oil displacement, primarily due to fracture orientations and density (less vertically oriented fractures or matrix system dominated reservoir sections). Additionally, regions dominated by vertical fractures, which contributed to long-term CO2 storage, were identified. The results of this work provide valuable insights for optimizing CO2 injection strategies and improving sweep efficiency, ultimately aiding in better decision-making for both enhanced recovery and greenhouse gas sequestration. This novel approach bridges the gap between data-driven analysis and traditional reservoir engineering principles, offering a scalable framework for CO2 EOR operations in fields with complex geologies.

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In terms of the collaborative optimization of CO2 flooding for Enhanced Oil Recovery (EOR) and CO2 sequestration, previous studies have co-optimized both cumulative oil production and CO2 sequestration by various algorithms. However, these solutions fail to optimize the CO2 injection schemes for high-water cut oil reservoirs. This paper presents an optimization methodology for CO2 flooding and sequestration in high-water cut oil reservoirs. The production optimization was carried out by adjusting the injection and production rate. To solve the proposed objective functions, the simultaneous perturbation stochastic approximation (SPSA) algorithm is applied in this paper, and the CMG-GEM module is utilized to simulate the reservoir production performance. A typical high-water cut reservoir in the Shengli oilfield was used to verify the feasibility of the presented methodology. In this paper, the production performance and net present value (NPV) for continuous gas injection under different water cuts were analyzed. The optimal timing of transforming from water flooding to gas displacement for the high-water cut reservoir was optimized. In addition, the optimal water–gas ratios for Water-Alternating-Gas (WAG) flooding were determined. The sensitivity of NPV to gas injection price and carbon subsidy was analyzed. The results show that when the gas price is 0.178 $/m3 and the carbon subsidy is 0.0169 $/m3, the optimal timing of transforming from water flooding to gas injection should be earlier than the time when the water cut is 0.82. Through the combination of NPV, cumulative oil production rate, and CO2 sequestration volume for WAG flooding, the optimal WAG ratio should be 1:2. The presented method in this paper considers various economic indicators and can optimize CO2 flooding and sequestration in high-water cut oil reservoirs efficiently, which can provide some guidance for the design of CO2 flooding schemes in high-water cut oil reservoirs.

The integration of advanced computational techniques with traditional reservoir engineering practices has revolutionized the field of enhanced oil recovery (EOR), particularly in the context of carbon sequestration. This study integrates machine learning (ML) algorithms and 3D visualization techniques to optimize CO2 sequestration and enhanced oil recovery (CO2-EOR) in the depleted Balkasar Oil Field, located in Pakistan's Potwar Basin. The application of ML, including neural networks and decision trees, allowed for the detailed analysis of extensive datasets comprising well logs, seismic surveys, and petrophysical measurements. The algorithms uncovered complex relationships between key reservoir properties, such as porosity, permeability, and hydrocarbon saturation, enabling precise predictions of hydrocarbon-bearing zones and dynamic fluid behaviors. A 3D geomechanical grid was constructed to visualize subsurface heterogeneities, including fault zones and fluid distribution, aiding in the identification of optimal CO2 injection zones. Simulations conducted on this grid revealed a recovery efficiency enhancement exceeding 30%, confirming the potential for significant hydrocarbon recovery. Moreover, pressure monitoring and CO2 plume migration predictions validated the integrity of sequestration, with stable storage observed under varying injection scenarios. The study's findings underscore the transformative potential of integrating advanced computational tools with traditional reservoir engineering methods. For instance, dynamic modeling in the Chorgali and Sakesar formations identified zones with high hydrocarbon retention, ensuring strategic injection planning. The multivariate fitting method demonstrated robust predictions of organic carbon content, essential for assessing the reservoir's remaining hydrocarbon potential. The transition toward sustainable energy practices necessitates innovative strategies that simultaneously address the imperatives of carbon reduction and efficient hydrocarbon recovery. The global energy sector is facing increasing pressure to mitigate climate change while meeting growing energy demands (Earlougher, 1977). This process involves injecting CO2 into depleted oil fields, where it reduces oil viscosity, improving its flow to production wells (Bourdet, 2002). ML models, such as neural networks and decision trees, can uncover hidden patterns in the data, improving the accuracy of reservoir predictions and optimizing CO2-EOR strategies (Manrique et al., 2007).

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CO2-assisted steam huff and puff is an effective method to improve oil recovery and store CO2 in heavy oil reservoirs. However, few studies focused on complex geological formations, such as bottom water. The bottom water condition not only complicates the process of oil production and CO2 sequestration, but also makes migration and distribution of oil, water and CO2 unclear. In this paper, a numerical geological model of an offshore heavy oil reservoir with bottom water is established to analyze the influence of bottom water on injection and production parameters, oil recovery and CO2 storage capability under vertical and horizontal well layouts. The results show that the bottom water could maintain the formation pressure, but reduce the steam chamber radius and heavy oil utilization area, increase water production and decrease the oil–water ratio. CO2 could enhance oil recovery in the bottom water reservoir. Oil development indicators of the horizontal well are higher than the vertical well. Meanwhile, CO2-assisted steam huff and puff use in the bottom water reservoir can create a high-pressure and -temperature environment to make CO2 supercritical, as it has better CO2 storage capability and efficiency. The CO2 storage efficiency of the horizontal well is 63% larger than the vertical well. Thus, the horizontal well layout should be used as a priority if bottom water presents. Conducted analysis of bottom water formation sensitivity parameters shows that the advantageous formation conditions are high oil saturation, porosity of 0.2–0.4 and permeability of 2000–3000 mD. The influence degrees of each formation parameter were evaluated as well.

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This study targeted a highly water-sensitive reservoir with high clay content (average 23.87%, mainly montmorillonite and illite), where waterflooding development induces hydration swelling of clay minerals, leading to pore-throat narrowing. The anti-swelling system and CO₂ were found to mitigate this phenomenon. The research investigated the dissolution, diffusion, and synergistic effects of CO₂ in the anti-swelling system/crude oil within the context of Carbon Capture, Utilization and Storage-Enhanced Oil Recovery (CCUS-EOR). Using the pressure decay method, core flooding experiments, microscopic visualization of oil displacement, and an improved mathematical model. We systematically investigated the influence of clay minerals on the balance between CO₂ storage and enhanced oil recovery (EOR). It was found that the diffusion coefficient of supercritical CO₂ increased rapidly and then levelled off with increasing pressure, which indicated that clay minerals hindered CO₂ diffusion. The anti-swelling system increases the effective pore connectivity by suppressing clay swelling, which increases the diffusion coefficient by 20–28%. The enhanced mathematical model combines the oil-water phase partition coefficients with the PR-EOS equation of state to accurately describe the multiphase interactions. The calculation results fit the experimental data by 92%, which is better than the traditional single-phase model. Through microscopic oil displacement experiments, core flooding tests, and quantitative analysis of full-cycle CO₂ saturation evolution. It is demonstrated that the sweep efficiency is anti-swelling system-CO₂ flooding is a higher sweep efficiency (73.95%) and achieves 58.12% oil recovery and 46.16% CO2 sequestration efficiency in a core with a permeability of 102.95 × 10−3 μm². The full-cycle CO2 saturation change rule was quantified, and the saturation cloud map was drawn. It is proven that the technology has the synergistic mechanism of ‘stabilising pore structure-reducing oil viscosity-efficient sequestration’, which combines significant oil recovery and carbon sequestration benefits, and provides theoretical and practical guidance for the low-carbon development of strong water-sensitive oilfields.

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In recent years, gas injection, especially CO2 injection, has been acknowledged as a promising approach for enhanced oil recovery (EOR) and CO2 capture and storage (CCS), especially for tight reservoirs. However, when CO2 is injected into the oil reservoirs, it can disturb the equilibrium of the system and lead to chemical reactions between CO2, formation water, and reservoir rocks. The reactions will alter some geochemical and physicochemical characteristics of the target reservoirs. However, the reactions still lack quantitative characterization at the pore scale, especially under reservoir conditions. Herein, we conducted an experimental study of the interactions between CO2, brine, and rocks in the Mahu oilfield at 20 MPa and 70 °C. The low-field nuclear magnetic resonance (LF-NMR) measurements showed that the incremental amplitude for tight cores of CO2–rock–water tests was larger than that for CO2–rock tests, and the amplitude alteration presented significant differences corresponding to different types of minerals and pores. Furthermore, the interplanar spacing of the core samples was increased with the increase of reaction time in the CO2–rock experiments but still lower than that in CO2–rock–water tests. This research demonstrated evident changes in the geochemistry in tight reservoirs caused by CO2, brine, and rock reactions. The results of this study may provide a significant reference for the exploration of similar reservoirs in the field of CO2–EOR and CO2 sequestration.

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Residual oil zones (ROZ) arise under the oil–water contact of main pay zones due to diverse geological conditions. Historically, these zones were considered economically unviable for development with conventional recovery methods because of the immobile nature of the oil. However, they represent a substantial subsurface volume with strong potential for CO2 sequestration and storage. Despite this potential, effective techniques for assessing CO2-EOR performance coupled with CCUS in ROZs remain limited. To address this gap, this study introduces a machine learning framework that employs artificial neural network (ANN) models trained on data generated from a large number of reservoir simulations (300 cases produced using Latin Hypercube Sampling across nine geological and operational parameters). The dataset was divided into training and testing subsets to ensure generalization, with key input variables including reservoir properties (thickness, permeability, porosity, Sorg, salinity) and operational parameters (producer BHP and CO2 injection rate). The objective was to forecast CO2 storage capacity and oil recovery potential, thereby reducing reliance on time-consuming and costly reservoir simulations. The developed ANN models achieved high predictive accuracy, with R2 values ranging from 0.90 to 0.98 and mean absolute percentage error (MAPRE) consistently below 10%. Validation against real ROZ field data demonstrated strong agreement, confirming model reliability. Beyond prediction, the workflow also provided insights for reservoir management: optimization results indicated that maintaining a producer BHP of approximately 1250 psi and a CO2 injection rate of 14–16 MMSCF/D offered the best balance between enhanced oil recovery and stable storage efficiency. In summary, the integrated combination of reservoir simulation and machine learning provides a fast, technically robust, and cost-effective tool for evaluating CO2-EOR and CCUS performance in ROZs. The demonstrated accuracy, scalability, and optimization capability make the proposed ANN workflow well-suited for both rapid screening and field-scale applications.

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Because it is necessary to focus on differences in regional oil reservoirs and determine the priority of the CCUS‐EOR (Carbon capture, utilization, and storage‐enhanced oil recovery) deployment under China's net‐zero CO2 emission target, systematic and regional evaluations of CO2 sequestration capacity in major oil basins are needed considering the geofluid properties—carbon sequestration capacity in place (CSCIP)—where the ‘in place’ indicates actual geological formation conditions underground, e.g., formation temperature and pressure. Therefore, physical properties of geofluids at different depths with different geologic temperatures and pressure conditions are considered for the CO2 sequestration capacity evaluation in place, including shallow (800–2000 m), medium (2000–3500 m), deep (3500–4500 m) and ultra‐deep (4500–8000 m) depth intervals. A modified evaluation model with four grading levels is proposed, combining the P‐V‐T equations of state (EOS) and evaluation equations of the Carbon Sequestration Leadership Forum (CSLF), including theoretical, effective, practical, and CCUS‐EOR CSCIP, which is more consistent with geofluid physical properties underground, to make the grading evaluation and ranking of the CSCIP in China's major oil basins. Then, the grading CSCIP of 29 major oil basins in China was evaluated based on the petroleum resources evaluation results of the Ministry of Natural Resources of China (MNRC) during China's 13th Five‐Year Plan period. According to the grading evaluation results, suggestions for China's CCUS‐EOR prospective regions are given as follows: shallow oil fields of the Songliao Basin in Northeast China, shallow–medium oil fields of the Bohai Bay Basin in East China, medium oil fields of the Zhungeer Basin in West China, and medium oil fields of the Ordos Basin in Central China; all are potential areas for the CCUS‐EOR geological sequestration in China's onshore oil basins. In addition, in China's offshore oil basins, shallow–medium oil fields of the Bohai Sea and shallow oil fields of the Pearl River Mouth Basin have potential for CCUS‐EOR geological sequestration.

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CO2-responsive foam (CRF) is a highly promising candidate for CO2-enhanced oil recovery (CO2-EOR) because it displays higher stability than the surfactant-stabilized foam owing to the formation of robust wormlike micelles (WLMs) upon exposure to CO2. In this work, the nanoparticle-enhanced CO2-responsive foam (NECRF) was properly prepared using lauryl ether sulfate sodium (LES)/diethylenetriamine/nano-SiO2, and its interfacial properties and EOR potential were experimentally and numerically assessed, aiming to explore the feasibility and effectiveness of NECRF as a novel CO2-EOR technique. It was found that the interfacial expansion elastic modulus increased 6-fold after CO2 stimulation. The modulus continued to increase with the introduction of nano-SiO2 owing to the pronounced synergistic effect of WLMs and nanoparticles. In addition to increasing the viscosity of the foaming liquid, WLMs and nano-SiO2 enhanced the shearing resistance of the NECRF as well. Calculations demonstrated that both the coarsening rate and the size distribution uniformity coefficient of NECRF were markedly lower than that of the LES foam, which subsequently inhibited NECRF decay and greatly improved its dynamic stability. Besides, molecular dynamics simulation revealed that adding inorganic salts to NECRF could notably enhance the foaming performance due to the intensified hydration of surfactant head groups and reduced binding energy of neighboring molecules. Nuclear magnetic resonance-assisted core flooding experiments validated the exceptional capacity of NECRF to sweep the low-permeability region and improve the conformance profile. Overall, these findings may provide valuable insights into the development and application of novel materials and strategies for the CO2-EOR.

This study investigates the impact of CO2-enhanced oil recovery (CO2-EOR) on the petrophysical properties and oil recovery potential of sandstone reservoirs in the oilfields located in the east-southern Precaspian region of Kazakhstan. Despite the recognized potential of CO2-EOR for improving oil recovery and aiding carbon sequestration, there is limited understanding of how CO2-EOR specifically affects the petrophysical properties of sandstone reservoirs in this region. Laboratory experiments were conducted using two core samples from the selected oilfields to examine changes in porosity, permeability, and oil recovery coefficients. The results demonstrated that porosity changes ranged from a slight increase of 1.1% to a decrease of 1.5%, while permeability reduction was significant, with decreases ranging from 29% to 50% due to clay alteration and halite precipitation. The oil recovery coefficient after CO2 flooding was found to be between 0.49 and 0.54. These findings underscore the complex interactions between CO2 and reservoir rocks, emphasizing the need for tailored EOR strategies in different geological settings.

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Hydraulic fracturing has enabled production from unconventional reservoirs in the U.S., but production rates often decline sharply, limiting recovery factors to under 10%. This study proposes an optimization workflow for the CO2 huff-n-puff process for multistage-fractured horizontal wells in the Wolfcamp A formation in the Delaware Basin. The potential for enhanced oil recovery and CO2 sequestration simultaneously was addressed using a coupled geomechanics–reservoir simulation. Geomechanical properties were derived from a 1D mechanical earth model and integrated into reservoir simulation to replicate hydraulic fracture geometries. The fracture model was validated using a robust production history matching. A fluid phase behavior analysis refined the equation of state, and 1D slim tube simulations determined a minimum miscibility pressure of 4300 psi for CO2 injection. After the primary production phase, various CO2 injection rates were tested from 1 to 25 MMSCFD/well, resulting in incremental oil recovery ranging from 6.3% to 69.3%. Different injection, soaking and production cycles were analyzed to determine the ideal operating condition. The optimal scenario improved cumulative oil recovery by 68.8% while keeping the highest CO2 storage efficiency. The simulation approach proposed by this study provides a comprehensive and systematic workflow for evaluating and optimizing CO2 huff-n-puff in hydraulically fractured wells, enhancing the recovery factor of unconventional reservoirs.

Geological storage of CO2 in offshore deep saline aquifers is widely recognized as an effective strategy for large-scale carbon emission reduction. This study aims to assess the mechanical integrity and storage efficiency of reservoirs using a multi-layer CO2 injection method in the Enping 15-1 Oilfield CO2 storage project which is the China’s first offshore carbon capture, utilization, and storage (CCUS) demonstration. A coupled Hydro–Mechanical (H–M) model is constructed using the TOUGH-FLAC simulator to simulate a 10-year CO2 injection scenario, incorporating six vertically distributed reservoir layers. A sensitivity analysis of 14 key geological and geomechanical parameters is performed to identify the dominant factors influencing injection safety and storage capacity. The results show that a total injection rate of 30 kg/s can be sustained over a 10-year period without exceeding mechanical failure thresholds. Reservoirs 3 and 4 exhibit the greatest lateral CO2 migration distances over the 10-year injection period, indicating that they are the most suitable target layers for CO2 storage. The sensitivity analysis further reveals that the permeability of the reservoirs and the friction angle of the reservoirs and caprocks are the most critical parameters governing injection performance and mechanical stability.

With the development of monitoring tools, temperature analysis is increasingly used to evaluate the characteristics of reservoirs and near-wellbore areas during CO2 injection. When carbon dioxide is injected into multi-layered saline aquifers, vertical heterogeneity leads to an uneven distribution of injection rate in each layer. Therefore, the monitoring of migration is of great significance for improving the CO2 storage capacity of saline aquifers. This paper proposes an analysis method of temperature recovery that considers capillary force and mutual solubility of CO2 and brine. Firstly, based on the gas-water two-phase flow in the saline aquifer, the aquifer is divided into three regions. The analytical solution of temperature change is established on the basis of three regions, and its accuracy is verified by numerical simulation. The CO2 injection rate and the thermal radius are obtained by analytical inversion of the transient temperature. The results show that the temperature profiles obtained by the analytical model are different around the thermal front. The location of thermal radius is greater than the radius of the dry-up zone, and the heat storage capacity of the reservoir rock causes the distance of CO2 migration to be greater than the distance of reservoir temperature change. Due to the temperature difference between the initial temperature of the aquifer and the temperature of the injected CO2, there is a smaller saturation front at the thermal front. This model can be applied to monitor multilayer CO2 injection profiles during the early stages of injection, providing a basis for adjusting the injection profile to enhance CO2 storage capacity.

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Multi-stage fractured horizontal well technology is an effective development method for unconventional reservoirs; however, shale oil reservoirs with ultra-low permeability and micro/nanopore sizes are still not ideal for production and development. Injecting CO2 into the reservoir, after hydraulic fracturing, gas injection flooding often produces a gas channeling phenomenon, which affects the production of shale oil. In comparison, CO2 huff-n-puff development has become a superior method in the development of multi-stage fractured horizontal wells in shale reservoirs. CO2 huff and injection can not only improve shale oil recovery but also store the CO2 generated in industrial production in shale reservoirs, which can reduce greenhouse gas emissions to a certain extent and achieve carbon capture, utilization, and storage (CCUS). In this paper, the critical temperature and critical parameters of fluid in shale reservoirs are corrected by the critical point correction method in this paper, and the influence of reservoir pore radius on fluid phase behavior and shale oil production is analyzed. According to the shale reservoir applied in isolation to the actual state of the reservoir and under the condition of a complex network structure, we described the seepage characteristics of shale oil and gas and CO2 in the reservoir by embedding a discrete fracture technology structure and fracture network, and we established the numerical model of the CO2 huff-n-huff development of multi-stage fractured horizontal wells for shale oil. We used the actual production data of the field for historical fitting to verify the validity of the model. On this basis, CO2 huff-n-puff development under different gas injection rates, huff-n-puff cycles, soaking times, and other factors was simulated; cumulative oil production and CO2 storage were compared; and the influence of each factor on development and storage was analyzed, which provided theoretical basis and specific ideas for the optimization of oilfield development modes and the study of CO2 storage.

Separate-layer CO2 flooding has increasingly been used to improve the overall development of multi-layer heterogeneous reservoirs. Due to their field technical limitations, layer combinations have to be carried out to reduce the number of layer-groups required for the separate injection of CO2. Currently there are few studies of the method of designing layer combinations. In field practice, the layer combinations are often made based on the permeability ratio of the layers to be developed, but it is not possible to accurately obtain the optimal scheme in many cases. Therefore, in this paper, a new design and optimization method based on the weighted standard deviation of permeability is proposed, which comprehensively considers the effects of multiple geological and fluid properties in different layers. The new method is applied to study the layer combination schemes in separate-layer CO2 flooding in H block, Daqingzijing Oilfield, Jilin, China. The prioritization of all of the schemes is obtained via the method, and a related numerical model is also established to perform verification and quantitative analysis. The results show that designing layer combinations using the new proposed method can achieve better development effect than using the conventional permeability ratio based method. It can achieve a more uniform interlayer CO2 displacement with an obvious improvement in the CO2 swept volume in low permeability layers and a higher overall oil recovery. According to the numerical simulation results, using the optimal layer combination scheme designed via the new proposed method, the ten-year swept volume of CO2 in the low permeability layer can be increased by 16.2%, and the ten-year overall oil recovery efficiency can be increased by 3.3%, with both measures showing a remarkable improvement. The work can provide a significant reference point for the field design of layer combinations in separate-layer CO2 flooding.

Carbon Capture, Utilization, and Storage (CCUS) projects require accurate subsurface data to ensure safe CO2 storage and efficient operations. To address the limitations of conventional sonic processing, a real-time digital acoustic work- flow was developed, integrating advanced signal processing and machine learning. Multi-Resolution Tracking (MRT) extracts high-resolution compressional and shear slowness, while machine learning-aided dipole inversion provides robust shear slowness and anisotropy classification across complex lithologies. Signal analysis with DTMTIV further improves horizontal slowness estimation in anisotropic or layered formations. Within hours of logging, processed outputs including P and S slowness, azimuthal anisotropy, and TI parameters are integrated into mechanical earth models to support real-time decision-making for stress testing, injection planning, and containment evaluation. Field applications demonstrate that this workflow accelerates data delivery, enables rapid quality control, and enhances geomechanical modeling. By improving stress profiling, anisotropy assessment, and shale characterization, the approach reduces uncertainty and contributes to safer and more efficient CCUS operations.

China's Yinggehai Basin gas field is in the middle and late stages of development and has a large CO2 sequestration potential. Moreover, the gas recovery is low, and it can be further enhanced by injecting CO2. In order to study the recovery ratio of the gas field and realize CO2 storage, numerical simulation studies were carried out on three types of gas reservoirs in Dongfang A gas field, including hypotonic, mesotonic depletion, and mesotonic water intrusion. The results show that: (1) competitive adsorption improves CO2 storage and CH4 recovery in low‐permeability gas reservoirs; CO2 injection can effectively supplement the formation energy, and competitive adsorption and pressurization are the main controlling factors for the development of low‐permeability gas reservoirs; (2) the recovery mechanism of medium permeability depleted gas reservoirs is to improve pressure and energy. Adsorption has almost no effect on methane recovery and cumulative production, and gas injection rate and gas injection components are the main controlling factors affecting CO2 sequestration; (3) CO2 injection in medium‐permeability water intrusion gas reservoirs can inhibit water intrusion. The higher the injection–production ratio, the better the effect of inhibiting water intrusion. CO2 should be injected into the gas layer in the process of gas injection development, and the injection‐production ratio and the gas injection components are the main controlling factors to improve CO2 storage. It is concluded that CO2 injection can improve pressure and energy, inhibit water intrusion, enhance gas recovery, and realize carbon sequestration, which makes CCUS‐EGR expected to be a potential technology for the stable and increased natural gas production in the Yinggehai Basin and provides a theoretical basis for the further development of the integrated technology of gas injection, recovery, and sequestration.

CCUS-EOR technology, as a core application of Carbon Capture, Utilization and Storage (CCUS), serves dual purposes of enhancing oil recovery and enabling geological sequestration of CO2. The multilayer CO2 injection into heterogeneous reservoirs technology achieves balanced displacement control by injecting tailored CO2 volumes into layers with heterogeneous permeability, thereby enabling precise regulation of reservoir dynamics. Field monitoring data indicate multiple wellbore integrity risks during CO2 injection operations, including engineering challenges such as packer failure. This study develops a coupled wellbore-reservoir model to analyze fluid flow, heat transfer, and mechanics during CO2 injection in a multilayer reservoir. The effects of injection parameters on wellbore flow behavior and the mechanical responses of completion wellbore are systematically investigated. Model validation against field measurements and commercial software benchmarks demonstrated a relative average error of less than 5% in predicting pressure and temperature distributions. When CO2 reaches the target injection zone, the reduction in flow rate prolongs the heat exchange duration between the fluid and reservoir, thereby enhancing the heating rate. The constraining effect of the packer induces an abrupt variation in the axial force of the tubing at its installation location. Wellhead injection pressure is primarily governed by injection gas composition and temperature. Reducing CO2 purity from 100% to 80% necessitates approximately 5 MPa additional pressure compensation at the wellhead. Injection rate critically influences the wellbore temperature profile through modulation of CO2 flow velocity. Namely, increasing injection flow rate from 5×104 to 17×104 m3/d will lead to 12 °C bottomhole temperature differential. Injection temperature affects tubing axial stress, where a 60 °C injection temperature increment (0–60 °C) results in a 103% elevation in axial stress at the wellhead. The proposed framework provides a robust quantitative tool for evaluating injection pressure requirements and wellbore mechanical responses under variable injection parameters, offering a decision-support foundation for optimizing multilayer CO2 injection processes in CO2 -EOR applications.

Carbon Capture, Utilization, and Storage (CCUS) stands as one of the effective means to reduce carbon emissions and serves as a crucial technical pillar for achieving experimental carbon neutrality. CO2-enhanced oil recovery (CO2-EOR) represents the foremost method for CO2 utilization. CO2-EOR represents a favorable technical means of efficiently developing extra-low-permeability reservoirs. Nevertheless, the process known as the direct injection of CO2 is highly susceptible to gas scrambling, which reduces the exposure time and contact area between CO2 and the extra-low-permeability oil matrix, making it challenging to utilize CO2 molecular diffusion effectively. In this paper, a comprehensive study involving the application of a CO2 nanobubble system in extra-low-permeability reservoirs is presented. A modified nano-SiO2 particle with pro-CO2 properties was designed using the Pickering emulsion template method and employed as a CO2 nanobubble stabilizer. The suitability of the CO2 nanobubbles for use in extra-low-permeability reservoirs was evaluated in terms of their temperature resistance, oil resistance, dimensional stability, interfacial properties, and wetting-reversal properties. The enhanced oil recovery (EOR) effect of the CO2 nanobubble system was evaluated through core experiments. The results indicate that the CO2 nanobubble system can suppress the phenomena of channeling and gravity overlap in the formation. Additionally, the system can alter the wettability, thereby improving interfacial activity. Furthermore, the system can reduce the interfacial tension, thus expanding the wave efficiency of the repellent phase fluids. The system can also improve the ability of CO2 to displace the crude oil or water in the pore space. The CO2 nanobubble system can take advantage of its size and high mass transfer efficiency, among other advantages. Injection of the gas into the extra-low-permeability reservoir can be used to block high-gas-capacity channels. The injected gas is forced to enter the low-permeability layer or matrix, with the results of core simulation experiments indicating a recovery rate of 66.28%. Nanobubble technology, the subject of this paper, has significant practical implications for enhancing the efficiency of CO2-EOR and geologic sequestration, as well as providing an environmentally friendly method as part of larger CCUS-EOR.

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CO2-EOR is one of the principal techniques for enhanced oil recovery (EOR). The CO2 injection not only promotes oil recovery but also leads to greenhouse gas discharge reduction. Nonetheless, a key challenge in the CO2 flooding process is a premature CO2 breakthrough from highly permeable zones. In recent years, Inflow Control Devices, ICDs, have been used as a potential solution to mitigate an early gas breakthrough. The key and important parameter in ICDs installation is obtaining its opening flow area. The common ways to obtain the ICD flow area such as utilizing optimization algorithms are very complicated and time-consuming, and further these methods are not analytical. The aim of this work is to solve the mentioned challenges—postpone the breakthrough time in gas injection and present an easy, fast, and analytical technique for obtaining ICDs flow area. This paper presents a new analytical method for obtaining inflow control devices flow area for injection wells in an oil reservoir under CO2-EOR in order to balance the injected CO2 front movement in all layers. Then, in order to compare the advantages and disadvantages of the presented technique with other methods such as optimization algorithms, a case study has been done on a real reservoir model under CO2 injection. Later, the results of studied scenarios in the case studied are given and compared. The results show that by utilizing the proposed method recovery factor is raised by improving sweep efficiency, and the breakthrough time is more postponed compared to the other methods about 400 days. Further, the ICD flow area calculation takes 2 min by presented analytical techniques, but the optimization algorithm takes 4040 min to run the simulation model to find the ICD flow area. In the end, the findings of the presented analytical formula can help to set the ICD flow area very fast without the simulation and help researchers for a better quantitative understanding of parameters affecting the ICD flow area by the given formula such as reservoir permeability.

Carbon dioxide injection to improve oil recovery is an important link in carbon capture, utilization, and storage (CCUS) and an important means of tertiary oil recovery. Conducting gas injection profile logging in injection wells can reflect the inter-and intra-layer suction differences in gas injection wells, reveal the contradictions between injection and production, and provide a basis for gas plugging and profile control; The integrity of the wellbore is an important part of the storage stage of CCUS, which directly determines the burial and storage effect, and wellbore leakage directly affects the gas injection and oil displacement effect; The inspiratory index test can evaluate the formation's gas absorption capacity and provide a reasonable injection pressure of the formation at this stage. Since carbon dioxide gas usually exists in a supercritical fluid state in the wellbore, traditional logging techniques have certain limitations. This paper focuses on the adaptability research of pulse neutron oxygen activation logging principle and construction technology, and combined with the application example of gas injection wells in CCUS block of Huang3 District in Changqing Oilfield, it is clarified that the pulse neutron oxygen activation logging can be used to carry out suction profiling, suction index testing and wellbore integrity evaluation in carbon dioxide injection wells, and it has good application effects.

In this paper, an innovative multi-phase strategy is developed and numerically tested to optimize CO2 utilization and storage in an oil reservoir to support low carbon transition. In the first phase, the water-alternating-gas (WAG) injection is conducted to simultaneously store CO2 and produce crude oil in the reservoir from the respective injection and production wells. In the second phase, the injection and production wells are both shut in for some time to allow CO2 and water to be stratigraphically separated. In the third phase, CO2 is injected from the upper part of the reservoir above the separated water layer to displace water downwards, while fluids continue to be produced in the water-dominated zone from the lower part of the production well. Lastly, the production well is finally shut in when the produced gas–water ratio (GWR) reaches 95%, but CO2 injection is kept until the reservoir pressure is close to the fracture pressure of its caprocks. The numerical simulations show that implementing the proposed multi-phase strategy doubles CO2 storage in comparison to applying the WAG injection alone. In particular, 80% of the increased CO2 is stored in the third phase due to the optimized perforation. In addition, the CO2 injection rate in the last phase does not appear to affect the amount of CO2 storage, while a higher CO2 injection rate can reduce the CO2 injection time and accelerate the CO2 storage process. In the proposed strategy, we assume that the geothermal energy resources from the produced fluids can be utilized to offset some energy needs for the operation. The analysis of energy gain and consumption from the simulation found that at the early stage of the CO2-WAG phase, the energy gain mostly comes from the produced oil. At the late stage of the CO2-WAG phase and the subsequent phases, there is very little or even no energy gain from the produced oil. However, the geothermal energy of the produced water and CO2 substantially compensate for the energy loss due to decreasing oil production. As a result, a net energy gain can be achieved from the proposed multi-phase strategy when geothermal energy extraction is incorporated. The new multi-phase strategy and numerical simulation provide insights for practical energy transition and CO2 storage by converting a “to be depleted” oil reservoir to a CO2 storage site and a geothermal energy producer while enhancing oil recovery.

This study develops a field-based techno-economic model and decision framework for a CO2-enhanced oil recovery and storage project under joint market uncertainty. Historical drilling and completion expenditures calibrate investment cost functions, and three years of production data are fitted with segmented hyperbolic Arps curves to forecast 20-year oil output. Markov-chain models jointly generate internally consistent pathways for crude oil, ETA, and purchased CO2 prices, which are embedded in a Monte Carlo valuation. The framework outputs probability distributions of NPV and deferral option value; under the mid scenario, their mean values are USD 18.1M and USD 2.0M, respectively. PRCC-based global sensitivity analysis identifies the dominant value drivers as oil price, CO2 price, utilization factor, oil density, pipeline length, and injection volume. Techno-economic boundary maps in the joint oil and CO2 price space then delineate feasible regions and break-even thresholds for key design parameters. Results indicate that CCUS-EOR viability cannot be inferred from oil price or any single cost factor alone, but requires coordinated consideration of subsurface constraints, engineering configuration, and multi-market dynamics, including the value of waiting in unfavorable regimes, contributing to low-carbon development and sustainable energy transition objectives.

No abstract available

The injection of CO2 into deep saline aquifers for geological carbon sequestration is being developed worldwide as a large-scale technology to reduce the greenhouse effect. Successful management of such industrial-scale projects requires accurate characterization of reservoir dynamic properties. However, a literature review shows a lack of CO2-brine relative permeability (kr) measurements under reservoir conditions for most storage cases, as well as a non-consensus on the measurement methods that partially explain the discrepancies observed in published results. The objectives of the work presented here are to reconciliate these methods and to suggest “best practices” when measuring kr curves with CO2. CO2/brine kr curves have been measured using two protocols (steady-state (SS) and unsteady-state (USS) methods) on a homogenous Grès-de-Fontainebleau sandstone. Experiments were conducted at reservoir conditions (54°C, 90 bars) using the mini-coreflood injection platform CAL-X™ (Youssef et al., 2018). This setup limits the plug size to a typical core length of 20 mm but provides qualitative access to the local saturations. We found that the combination of the different methods (SS and USS) allows us to derive the most reliable curves. As experiments on small samples are an order of magnitude faster than those measured on standard samples, the combination of these methods is made possible in a reasonable time (a few days). Finally, using two-dimensional (2D) radiography to monitor local saturation has been demonstrated to be a key element for the kr curves or the capillary pressure (Pc) curves interpretations. It provides the possibility to quality check the displacement homogeneity, in both radial and vertical directions.

Carbon dioxide (CO2) storage capacity in saline aquifers is limited by the increase in reservoir pressure as CO2 is injected. Extraction of reservoir brine is an option to manage this pressure and maximize CO2 storage. In the UK North Sea, Endurance is the largest and best-appraised saline aquifer CO2 store. This paper assesses the option to extract brine from Endurance and substantially increase its storage potential. The focus is the management of this highly saline brine: discharge offshore, re-injection or treatment onshore? Three main strands of work informed the assessment: Quantification of the potential environmental impact of offshore discharge, via Whole Effluent Toxicity (WET) testing, flume tank experiments on dilution of surface and subsea brine discharges, changes in metal speciation and bioavailability during mixing and modelling of mineral precipitation, and modelling of brine discharge mixing with seawater using the Dose-related Risk and Effects Model (DREAM). Conceptual engineering and costing of the three main brine management options: offshore discharge, brine re-injection into a secondary reservoir, and onshore brine treatment. "Best Practicable Environmental Option" assessment, comparing the advantages and disadvantages of each of the potential brine management methods. This paper highlights the complex balance between managing potential environmental impacts, stakeholder views and regulatory requirements, whilst delivering an economically efficient and technically robust brine management concept. Re-injection via nearby facilities ranks as the best option, eliminating any potential environmental impact caused by toxicity of the brine, although technical feasibility and safety risks are increased. Onshore treatment is a relatively lower cost option but requires an onward management and disposal of resultant waste streams following treatment that is unlikely to be an environmentally credible option. Offshore discharge is the lowest cost and most technically feasible option; however, potential environmental impact, along with reputational and regulatory risks, currently make this unattractive. This analysis underlines the additional risks from expanding carbon capture, use and storage (CCUS) projects to include brine management within their scope. The study informed long-term development choices made for the Northern Endurance Partnership (NEP), resulting in acquisition of additional carbon storage licences to ensure sufficient CO2 storage capacity without the need for brine extraction. The environmental testing and modelling of brine discharge extends industry knowledge in a new and important area, as most of the future CO2 storage capacity in the UK North Sea resides in saline aquifers. Regulatory clarity on the toxicity assessment techniques and the constraints/limits to be imposed on any brine discharge is required for brine management to be considered within UK CCUS projects.

Conventional Carbon Capture and Storage (CCS) operations use the direct injection of CO2 in a gaseous phase from the surface as a carbon carrier. Due to CO2 properties under reservoir conditions with lower density and viscosity than in situ brine, CO2 flux is mainly gravity-dominated. CO2 moves toward the top and accumulates below the top seal, thus reinforcing the risk of possible leakage to the surface through unexpected hydraulic paths (e.g., reactivated faults, fractures, and abandoned wells) or in sites without an effective sealing caprock. Considering the risks, the potential benefits of the interplay between CO2 and an aqueous solution of formate ions (HCOO¯) were evaluated when combined to control CO2 gravity segregation in porous media. Three combined strategies were evaluated and compared with those where either pure CO2 or a formate solution was injected. The first strategy consisted of a pre-flush of formate solution followed by continuous CO2 injection, and it was not effective in controlling the vertical propagation of the CO2 plume. However, the injection of a formate solution slug in a continuous or alternated way, simultaneously with the CO2 continuous injection, was effective in slowing down the vertical migration of the CO2 plume and keeping it permanently stationary deeper than the surface depth.

This paper presents experimental and numerical sensitivity studies to assist injection strategy design for an ongoing CO2 foam field pilot. The aim is to increase the success of in-situ CO2 foam generation and propagation into the reservoir for CO2 mobility control, enhanced oil recovery (EOR) and CO2 storage. Un-steady state in-situ CO2 foam behavior, representative of the near wellbore region, and steady-state foam behavior was evaluated. Multi-cycle surfactant-alternating gas (SAG) provided the highest apparent viscosity foam of 120.2 cP, compared to co-injection (56.0 cP) and single-cycle SAG (18.2 cP) in 100% brine saturated porous media. CO2 foam EOR corefloods at first-contact miscible (FCM) conditions showed that multi-cycle SAG generated the highest apparent foam viscosity in the presence of refined oil (n-Decane). Multi-cycle SAG demonstrated high viscous displacement forces critical in field implementation where gravity effects and reservoir heterogeneities dominate. At multiple-contact miscible (MCM) conditions, no foam was generated with either injection strategy as a result of wettability alteration and foam destabilization in presence of crude oil. In both FCM and MCM corefloods, incremental oil recoveries were on average 30.6% OOIP regardless of injection strategy for CO2 foam and base cases (i.e. no surfactant). CO2 diffusion and miscibility dominated oil recovery at the core-scale resulting in high microscopic CO2 displacement. CO2 storage potential was 9.0% greater for multi-cycle SAGs compared to co-injections at MCM. A validated core-scale simulation model was used for a sensitivity analysis of grid resolution and foam quality. The model was robust in representing the observed foam behavior and will be extended to use in field scale simulations.

This paper presents an innovative modeling of continuous fiber-optic measurements to improve the dynamic characterization of injection wells during the early stages of carbon capture and storage (CCS) projects. The approach uses distributed temperature sensing (DTS) data collected along the well profile to map the thermal behavior in real time during three key phases: before injection begins, during the initial regime when carbon dioxide (CO2) displaces the brine in the tubing and fills the borehole, and during full stable operation. This physics-based methodology provides fluid mapping based on DTS, as well as a comprehensive description of the well thermal performance, essential for understanding and optimizing CO2 injection. The results obtained during CO2 injection into a depleted natural gas reservoir demonstrate the present method. The injection well completion is equipped with permanent fiber-optic cables for continuous DTS monitoring down to the production packer. While standard DTS can be used to monitor the well thermal performance during steady-state operations, other factors are essential for accurately monitoring the distributed temperature profile during transient operations. This study begins with an analysis of brine displacement from the tubing into the borehole during well commissioning. The dynamic behavior of CO2 during these operations led to thermal effects along the well tubing, which were addressed through an innovative analysis of DTS data. A reprocessing of the space-time temperature measurements was implemented to distinguish between the downward movement of gas and liquid within the tubing. This made it possible to locate the real-time position of the contact between CO2 and brine in the tubing, thanks to their different physical properties. DTS measurements and reprocessing outputs were successfully used to calibrate a physics-based well simulation model that describes fluid dynamics and thermodynamics, involving complex well geometries and multiphase flow conditions. Thus, the DTS-calibrated physics-based simulation model provided insight into the well’s thermal evolution and allowed for the real-time computation of important physical properties, such as the density, phase, and pressure profiles of CO2. The presented methodology provides strong dynamic characterization of CO2 injection wells from the beginning of a CO2 transportation and storage (T&S) project. The resulting calibrated wellbore models are essential for CO2 injection optimization, flow assurance, and risk management. While there are several approaches to maximize information from permanent DTS data, quantitatively using temperature evolution for dynamic modeling is a novel technology that can shed light on the early and uncertain stages of CO2 T&S projects.

Understanding CO 2 /brine relative permeability is crucial for modeling fluid flow in CO 2 storage projects, which directly impacts the assessment of storage capacity, maximum injection rates, plume migration, and area of review (AoR). The U

During CO 2 -saturated brine injection in deep saline aquifers, there is a potential occurrence of formation damage or permeability enhancement. This can be due to the reactive interaction between the injected CO 2 - saturated brine and the formation rock. Therefore, in this study, we aim to provide an integrated model that quantifies the impact of dissolution/precipitation of rock minerals during coupled convective, diffusive

CO 2 dissolution in the storage aquifer’s brine is one of the main CO 2 immobilization mechanisms in the subsurface. During injection, CO 2 dissolution is primarily governed by the contact area between the CO 2 and brine. Accordingly, when using finite-difference numerical simulation tools to model the CO 2 -brine displacement, the model discretization size affects the level of dissolution given that it controls the contact area. Grid size should be carefully selected to avoid unrealistic dissolution estimations. It is important to obtain an independent estimate of the dissolution using discretization-free analytical approaches. In this study, the author presents two analytical approaches to estimate the range of CO 2 dissolution. The first method assumes gravity-dominated flow, with a limited role for the capillary force in the vertical direction, resulting in vertical equilibrium modeling approach. The second assumes viscous-dominated flow with no role for gravity force, maximizing the CO 2 -brine contact area and dissolution rate through the fractional flow modeling approach. The two approaches are applied to an example CO 2 injection case and their resulting ranges are compared with estimates from numerical simulations considering different spatial discretizations. Numerical simulations show that large discretizations can result in unrealistic dissolution rates outside the analytically-driven range

No abstract available

Understanding two‐phase flow in porous media is essential for optimizing subsurface storage efficiency. Pore‐scale flow properties significantly influence macroscopic plume migration behavior and trapping performance. However, the inherent complexity of porous media impedes real‐time tracking of pore‐scale flow dynamics, leaving the mechanisms governing CO2‐brine steady‐state flow largely unexplored. In this study, CO2‐brine co‐injection experiments were conducted to explore fluid flow and distribution at the pore scale using X‐ray computed tomography (X‐ray CT) imaging. The results reveal that both the nonwetting and wetting phases, as well as the intermittent flow with CT grayscale values between those of nonwetting and wetting, are strongly affected by the capillary number. The nonwetting phase primarily occupies larger pores, while the wetting phase exhibits a bimodal distribution across small and big pores. This bimodal distribution is attributed to the core's heterogeneity and the presence of water layers along the pore walls, which also provides a unique insight into water layer identification at the pore scale. Additionally, the experiments reveal a distinct phenomenon where the morphology of the nonwetting phase transitions from clusters to singlets and then to ganglia as nonwetting phase capillary numbers vary. This transition highlights the role of the intermittent flow in modifying nonwetting phase morphology, leading to disconnections and reconnections that alter connectivity and relative permeability.

CO2 is highly effective at enhancing shale oil recovery while facilitating geological sequestration. The interaction between supercritical CO2 (ScCO2) and shale significantly alters the wettability, a key factor influencing both the oil recovery efficiency and the CO2 storage capacity. A novel investigation was carried out to explore the dynamic characteristics of the CO2–brine–oil–shale multiphase system and the mechanisms underlying wettability alteration using samples from the Yanchang shale formation in China. The wettability of shale samples was characterized by high-temperature and high-pressure contact angle tests, while quantitative analysis of the mineral composition was conducted through ScCO2-shale reaction experiments combined with XRD. FTIR and zeta potential tests determined the types and amounts of surface charged groups, and 3D surface morphology scanning reflected structural changes. Results showed that ScCO2 injection significantly weakened the water-wetness of shale. Temperature and pressure were key external factors: increasing temperature shifted the wettability from water-wet toward neutral-wet, while higher pressure drove it closer to oil-wet. After ScCO2 treatment, significant alterations in the physicochemical properties of shale were observed, which fundamentally influenced its wettability. The content of clay minerals, encompassing both hydrophilic and hydrophobic phases, was reduced, whereas the proportion of hydrophilic quartz increased. The decrease in hydrophilic hydroxyl groups (OH), increase in oleophilic oxygen-containing groups (C–O–C), and reduction in the zeta potential collectively altered the multiphase interfacial forces, thereby impacting the spreading behavior of liquids on shale surfaces. ScCO2 also increased shale surface roughness at the nanoscale, which can alter fluid distribution by providing additional adsorption sites and modifying the spreading behavior of fluids. These findings provide theoretical support for artificial wettability regulation, aiding shale oil recovery and CO2 storage.

The injection of CO₂ into carbonate reservoirs for long-term sequestration induces complex geochemical and geomechanical interactions at the pore scale, influencing storage capacity and reservoir integrity. This study presents a combined numerical and experimental approach to evaluating these interactions, focusing on mineral dissolution, precipitation, and their impact on permeability and mechanical stability. Laboratory-scale experiments using high-pressure flow cells and microfluidic devices simulate CO₂-brine-rock interactions under reservoir conditions. Advanced imaging techniques, including X-ray micro-computed tomography (µCT) and scanning electron microscopy (SEM), provide insights into pore-scale alterations and reaction dynamics. Complementing the experimental analysis, a numerical model incorporating reactive transport equations and geomechanical coupling is developed to predict dissolution patterns, permeability evolution, and rock strength variations. The Lattice Boltzmann Method (LBM) and Finite Volume Method (FVM) are employed to simulate multiphase flow and mineralogical changes over time. Model calibration with experimental data ensures accuracy in representing key processes such as acid-induced pore enlargement, precipitation of secondary minerals, and stress redistribution in the rock matrix. Results reveal that CO₂ injection leads to significant heterogeneities in pore structure, enhancing permeability in some regions while inducing mechanical weakening in others. These highlight the dual impact of CO₂ sequestration in carbonate formations: improved injectivity but potential risks to reservoir stability. Understanding these dynamics is crucial for optimizing storage strategies and mitigating leakage risks. This contributes to advancing predictive models for subsurface CO₂ sequestration, supporting the safe and efficient implementation of carbon capture and storage (CCS) technologies. Future research should refine upscaling methodologies and incorporate real-time monitoring techniques for improved assessment of CO₂ behavior in geological formations.

No abstract available

Injection of carbon dioxide (CO2) into subsurface reservoirs is a pivotal component of carbon capture, utilization, and storage (CCUS) technologies, aimed at mitigating the adverse impact of anthropogenic greenhouse gas emissions on climate change. A critical aspect influencing the efficacy of CCUS is the interaction between CO2 and brine within sandstone reservoirs, particularly how CO2 storage affects the wettability of the rock and, consequently, dynamics of fluid flow characterized by the relative permeability and capillary pressure. This study aims to quantitatively assess the steady-state relative permeability between CO2 and brine in Berea sandstone, a common analog for reservoir rocks, and the implications of it in CO2 storage. Prior to performing the dynamic flow tests, a detailed analysis, static reactivity of the rock-fluid system has been completed. Employing an advanced core flooding apparatus, complemented by gamma-ray scanning technology, we conducted a series of experiments to measure the CO2-brine relative permeability before and after a 30-day CO2 exposure under reservoir conditions (1500 psi and 150°F). This experimental setup allowed for precise, in-situ saturation measurements, providing a comprehensive understanding of the changes in fluid distributions and flow behavior induced by CO2 storage. Insights derived from this investigation are anticipated to significantly augment existing predictive models for CCUS, facilitating more accurate assessments of CO2 injection strategies and storage capacity of the potential reservoirs. By examining the relationship between CO2 storage and relative permeability, our research underscores the critical need for integrated approaches in the design and optimization of CCUS operations. Ultimately, this study contributes to advancing CCS technologies as an integral solution for the technical evaluation of the subsurface options for climate change mitigation, highlighting the nuanced interplay between geological and chemical processes in subsurface environments and scale-up processes.

According to a report by the International Energy Agency, global energy demand grew significantly in 2023 nearly doubling the average growth rate since 2010. This increase has intensified the release of anthropogenic CO2 into the atmosphere, accounting for about 80% of global greenhouse gas emissions. Similarly, emissions from fossil fuels used in energy production and consumption have pushed atmospheric CO2 concentrations to an alarming 422 ppm, with projections suggesting levels could rise to 600–700 ppm by the end of this century. Such an increase could result in a global temperature rise of 4.5–5°C, leading to severe environmental and economic consequences. To address this, carbon capture and storage (CCS) has emerged as a promising solution alongside energy efficiency improvements, renewable energy adoption, and large-scale afforestation. CCS involves capturing CO2 from fixed-point sources and injecting it into deep geological formations for long-term storage. Saline aquifers are particularly attractive for CCS due to their large regional extent and high porosity, offering substantial storage capacity. However, challenges such as aquifer structural uncertainty, injectivity loss, and leakage risks must be resolved to ensure the technology's feasibility and safety. This paper focuses on evaluating the impact of CO2-brine-rock interactions on the storage capacity and containment potential of saline aquifers in the Niger Delta. Using formation data from the region, a coupled wellbore-reservoir modelling was conducted with PROSPER and CMG software to simulate various injection scenarios and assess their effects on key parameters such as porosity, permeability, caprock integrity, and brine chemistry. Initial findings reveal that CO2 injection triggers complex chemical interactions that enhance storage capacity through mineral trapping but may reduce injectivity due to pore blockage caused by precipitation. Caprock integrity analysis shows that Niger Delta formations possess adequate sealing capacity, with minimal leakage risks under controlled injection rates. Residual and solubility trapping mechanisms further contribute to long-term CO2 containment. This paper provides valuable insights into the dynamic behaviour of CO2 storage in saline aquifers, offering a deeper understanding of site-specific factors that influence injectivity and containment. The results will guide the optimisation of CCS strategies in the Niger Delta, supporting the region's efforts to reduce carbon emissions and contribute to global climate goals.

CO2 injection into geological formation for carbon capture, utilization, and storage (CCUS) including enhanced oil or gas recovery provides a solution to reduce CO2 emissions and bring on potential economic benefits. However, field operation possesses potential challenges both for injection and production wells. Operational constraints commonly considered are weighted around the injection well and related to well and formation integrity (e.g., limiting the risk of injection-induced fracturing). On the other hand, complexities of CO2-brine-rock interaction affect sand production phenomena in production wells. This study investigates CO2-brine-rock interaction to reflect CO2 injection impact toward reservoir fluid and rocks. This study involves extensive experimental works, namely, time-lapse dry mass measurements, brine compositions and pH analysis, X-ray diffraction (XRD), scanning electron microscopy–energy-dispersive spectroscopy (SEM-EDS), petrographic thin section analysis, porosity measurements, and elastic wave velocity measurements. CO2-brine-rock batch experiment was designed and utilized to observe mineral dissolution, pore structure alteration, as well as rock physics alteration caused by CO2-brine-rock interactions. An outcrop sample of dolomite-rich sandstone in Air Benakat formation, South Sumatra, Indonesia, was used as a case study. This study shows that dolomite dissolution was observed and led to ∼6.6% porosity improvement as well as rock strength reduction (as shown by ∼4.3% of P wave and ∼6.2% of S wave reduction, respectively). The results of experimental works were then used to construct sand onset prediction model that considers rock strength alteration caused by CO2-brine-rock interactions. The sand onset prediction model demonstrates an acceleration of sand onset occurrence due to CO2-brine-rock interactions which can assist the operator to design a better sand management strategy in producer wells.

The CO2–brine–rock interaction can significantly alter rock permeability during CO2 storage in saline aquifers. However, quantitatively characterizing the effects of this interaction on the correlation between the microstructure of pores and permeability is still a challenge. To address this issue, this study focuses on sandstone core sampling from the CO2 saline aquifer storage field test site in the Dezhou subdepression, China. The microscopic pore structures of samples before and after CO2 injection were analyzed using x-ray micro-computed tomography imaging, and laboratory experiments simulating CO2–brine–rock interactions were conducted under normal temperature and pressure conditions. Additionally, permeability coefficients were evaluated by integrating fractal theory with numerical simulations. The results indicate that mineral dissolution caused by CO2–brine–rock interactions significantly enhanced pore connectivity by 233.50%, increased the maximum pore radius by 28.46%, and expanded the maximum throat radius by 60.81%. These microstructural modifications also led to a 9.87% increase in mean fractal dimension and a 213.25% improvement in mean permeability. Furthermore, the dynamic variation of fractal dimension was found to be a reliable indicator of interaction intensity. By coupling the evolution of fractal dimension with connected porosity, a new permeability prediction model was established to quantitatively assess the impact of CO2–brine–rock interactions. The model showed good agreement with experimental measurements. This study provides a practical methodology for quantifying permeability evolution driven by geochemical alteration and offers theoretical insights for enhancing the predictive accuracy of reservoir performance under reactive flow conditions in CO2 geological storage.

Abstract Carbon storage in saline aquifers is a prominent geological method for reducing CO2 emissions. However, salt precipitation within these aquifers can significantly impede CO2 injection efficiency. This study examines the mechanisms of salt precipitation during CO2 injection into fractured matrices using pore-scale numerical simulations informed by microfluidic experiments. The analysis of varying initial salt concentrations and injection rates revealed three distinct precipitation patterns, namely displacement, breakthrough and sealing, which were systematically mapped onto regime diagrams. These patterns arise from the interplay between dewetting and precipitation rates. An increase in reservoir porosity caused a shift in the precipitation pattern from sealing to displacement. By incorporating pore structure geometry parameters, the regime diagrams were adapted to account for varying reservoir porosities. In hydrophobic reservoirs, the precipitation pattern tended to favour displacement, as salt accumulation occurred more in larger pores than in pore throats, thereby reducing the risk of clogging. The numerical results demonstrated that increasing the gas injection rate or reducing the initial salt concentration significantly enhanced CO2 injection performance. Furthermore, identifying reservoirs with high hydrophobicity or large porosity is essential for optimising CO2 injection processes.

Injection of CO2-saturated brine into deep saline aquifers, one of the key components of carbon sequestration strategies, can significantly alter formation permeability through coupled geochemical reactions and fines migration. These changes can lead to either formation damage or stimulation, directly affecting injectivity and long-term storage performance and especially surface footprint. This study presents a comprehensive modeling and experimental approach to quantify the impact of mineral dissolution, precipitation, and fines migration during reactive, convective, and dispersive flow in sandstone reservoirs. A coupled numerical model integrates reactive transport equations with mineralogical kinetics, using saturation index calculations to predict dissolution and precipitation behavior. Permeability evolution is evaluated through the Kozeny–Carman relationship, while fines migration effects are incorporated using the Khilar and Fogler (1983) framework. Coreflood experiments under reservoir conditions were conducted for model development and validation. Two of the key elements of this process, the role of kaolinite and injection rate were further investigated by comparing numerical predictions and experimental outcomes across samples with various mineralogies. Post-injection diagnostics, including micro-CT imaging and geomechanical testing, provide insight into the physical drivers of permeability alteration. Results demonstrate that while conventional brine injection has a negligible impact, CO2-saturated brine (pH 3.2–4.4) can reduce permeability by up to 64%, with fines migration contributing more significantly than the impact of geochemical reactions. At low injection rates, however, fines migration becomes minimal. The presence of kaolinite mitigates permeability loss and, under certain conditions, enhances permeability due to its dissolution outweighing secondary mineral precipitation. This study provides critical insights into optimizing CO2-saturated brine injection by tailoring brine composition and injection strategies to minimize formation damage. Understanding permeability evolution during this process and the key parameters are essential for predicting near-wellbore behavior, maintaining injectivity, and improving the overall efficiency of carbon storage projects.

Predictive modeling of CO2 storage sites requires a detailed understanding of physico-chemical processes and scale-up challenges. Dramatic injectivity decline may occur due to salt precipitation pore clogging in high-salinity aquifers during subsurface CO2 injection. This study aims to elucidate the impact of CO2-induced salt crystallization in the porous medium on the geomechanical properties of reservoir sandstones. As the impact of salt precipitation cannot be isolated from the precursor interactions with CO2 and acidified brine, we present a comprehensive review and discuss CO2 chemo-mechanical interactions with sandstones. Laboratory geochemical CO2–brine–rock interactions at elevated pressures and temperatures were conducted on two sandstone sets with contrasting petrophysical qualities. Interaction paths comprised treatment with (a) CO2-acidified brine and (b) supercritical injection until brine dry-out, salt crystallization, and growth. Afterward, the core samples were tested in a triaxial apparatus at varying stresses and temperatures. The elastic moduli of intact, CO2-acidified brine treated, and salt-affected sandstones were juxtaposed to elucidate the geochemical–geomechanical-coupled impacts and identify the extent of crystallization damages. The salt-affected sandstones showed a maximum of 50% reduction in Young’s and shear moduli and twice an increase in Poisson’s ratio compared to intact condition. The deterioration was notably higher for the tighter reservoir sandstones, with higher initial stiffness and lower porosity–permeability. We propose two pore- and grain-scale mechanisms to explain how salt crystallization contributes to stress localization and mechanical damage. The results highlight the potential integrity risk imposed by salt crystallization in (hyper)saline aquifers besides injectivity, signaling mechanical failure exacerbated by pressure buildup. Geochemically induced mechanical alterations in saline aquifer sandstones near CO2 injection wellbores are explored. The impacts of treatment with CO2-acidified brine and CO2-induced salt precipitation in pore space are juxtaposed experimentally. Salt crystallization damage profoundly and distinctly impacted the elastic parameters of two sandstone classes. Marked decline in Young’s modulus and rigidity signals elevated risk of mechanical failure in carbon storage reservoirs. Pore- and grain-level damage mechanisms are observed and conceptualized to describe stress localization imposed by salt crystallization. Geochemically induced mechanical alterations in saline aquifer sandstones near CO2 injection wellbores are explored. The impacts of treatment with CO2-acidified brine and CO2-induced salt precipitation in pore space are juxtaposed experimentally. Salt crystallization damage profoundly and distinctly impacted the elastic parameters of two sandstone classes. Marked decline in Young’s modulus and rigidity signals elevated risk of mechanical failure in carbon storage reservoirs. Pore- and grain-level damage mechanisms are observed and conceptualized to describe stress localization imposed by salt crystallization.

No abstract available

Formation damage is a general term that describes factors harming well productivity and injectability. To mitigate the greenhouse effect caused by the presence of carbon dioxide (CO2) in the atmosphere, scientists have proposed storing CO2 in depleted oil and gas reservoirs, aiming to result in enhanced oil recovery (EOR). This approach, despite its benefits, can also result in formation damage, including salt precipitation, leading to reduced porosity and permeability, thereby affecting injectability and productivity. In this study, we used glass micromodels with homogeneous and heterogeneous patterns to comprehensively and visually investigate the salt precipitation during CO2 injection in carbon capture and storage (CCS) and EOR processes. In addition, we ivestigated virtually the impact of porous media type, brine concentration, CO2 injection flow rate, and different salt types, as well as a comparative analysis of these variables. Three different brines containing sodium chloride, calcium chloride, and potassium chloride were utilized, using reservoir oil experiments. With increasing salt concentration, salt precipitation increased in all parts of the porous media, and with increasing CO2 injection rate, the amount of salt precipitation decreased, especially at the entrance of the porous media. In the homogeneous micromodel, more salt precipitate formed than in the heterogeneous micromodel, and the distribution of salt precipitation was more regular because it had more regular pores and porosity. The amount of salt precipitation in CCS is more than in EOR because, in CCS, the amount of brines in pores is more. Sodium chloride salt caused more precipitation during CO2 injection due to its lower van der Waals radius than other salts. Carbon dioxide, Formation damage, CCS, EOR, Micromodel

This study investigated the effects of absolute permeability on the performance of continuous CO2 injection for a CO2‐enhanced oil recovery and storage process (CO2‐EOR and Storage) in a water‐invaded zone. First, the CO2 solubility in dead‐oil and brine samples and the oil swelling factor were measured using a visual high‐pressure–high‐temperature cell. Following this, several continuous immiscible CO2 injection core flooding tests at a constant rate of 0.5 cm3/min and in situ reservoir conditions were conducted. The core samples were taken from a carbonate depleted oil reservoir located in southern Iran. The results revealed that more than 30% of the injected CO2 was trapped primarily by residual‐phase and solubility‐trapping mechanisms. In addition, it was found that the core samples with lower absolute permeability provided higher storage efficiency. In contrast, the ones with the highest absolute permeability showed the least potential for CO2 storage. From the EOR point of view, on average, 18% of the residual oil was produced mechanistically through swelling as well as physical displacement. Although the results showed a declining trend in the amount of oil produced with increased absolute permeability, no clear relationship could be established.

Carbon Capture Utilization Storage (CCUS) into geological storage (e.g., Enhanced Oil or Gas Recovery) provides a solution to reduce CO­2 emissions. However, it still remains a potential operational problem, such as sand problem phenomena in producer wells.  This study observes the phenomenon of sand problems in production wells possibly triggered by CO2-brine-rock interactions on CO2 injection in rich dolomite sandstone reservoir. This research performs several experimental works (i.e., time-lapse dry mass measurements, X-Ray Diffraction (XRD), Scanning Electron Microscope (SEM), and elastic wave measurements) by using CO2-brine-rock batch experimental setup as well as geochemical simulation to observe mineral dissolution, pore structures alteration as well as rock physics alteration due to CO2-brine-rock interactions. We used an outcrop sample of dolomite-rich sandstone from the Air Benakat Formation, South Sumatera, Indonesia. Our experimental and simulation works show that dolomite dissolution (dolomite reduction of ~4% after 14 soaking days), secondary porosity development (11% of visible porosity improvement), as well as rock strength reduction, occur indirectly (shown by elastic wave velocity, i.e.  and  reduction of ~3.8% and ~4.4%, respectively) due to CO2-brine-rock interactions. Subsequently, the results of elastic wave velocity measurements were then used to modify a considerable sand onset prediction (sand-free envelope) model. The modified model showed that the production well was more prone to sand problems due to CO2-brine-rock interactions. Thus, it is concluded that the sand onset prediction model with considering CO2-brine-rock interactions could help to design a better sand management strategy in producer wells.

In the context of carbon capture, utilization, and storage (CCUS) integrated with enhanced oil recovery (EOR), achieving both high oil recovery and substantial carbon storage is a critical challenge. Conventional injection methods often entail trade-offs between these objectives. Continuous CO 2 injection typically favors CO 2 storage but limits oil recovery because of its inefficient volumetric sweep, while water-alternating-gas (WAG) injection tends to enhance oil recovery at the cost of reduced CO 2 storage. This study introduces a novel injection strategy, formate-alternating-gas (FAG), which alternates between CO 2 and an aqueous formate solution. Formate, a carbon carrier produced via CO 2 reduction reactions, is leveraged to achieve simultaneous enhancements in oil recovery and carbon storage compared to traditional methods. A compositional simulation model of a San Andres oil reservoir in the Permian Basin was developed to compare

Optimizing CO2 storage efficiency in Deep saline aquifers (DSA) involves improving each storage trapping mechanism, such as structural/stratigraphy, capillary/residual, mineral, and dissolution trapping mechanisms, while maintaining the reservoir integrity for long-term carbon capture and storage (CCS). These enhancements are driven by a series of geochemical reactions that favorably modify petrophysical, mineralogy, wettability, rock geomechanics of the rock, and dissolution of CO2 in aquifer fluid. Three different CO2 injection strategies have been identified and tested for optimizing CO2 storage and efficiency- Continuous CO2 injection (CCI), Water Alternating Gas (WAG), and Simultaneous scCO2-brine Aquifer Injection (SAI). This study investigates the effect of integrating produced water (PW) into WAG and SAI strategies for CO2 storage, emphasizing how the salinity of the injected water affects reservoir properties alterations in sandstone and limestone formations exposed to scCO2. Experimental results show that high salinity levels accelerate mineralogy changes and wettability alteration, particularly in limestone, leading to porosity, permeability, and mechanical strength changes. While the SAI results showed more aggressive and detrimental changes in rock properties, WAG leads to slower reaction rates, a more stable and effective strategy with more gradual alterations in rock properties due to its ability to balance fluid flow and mechanical strength, hence offering greater stability for long-term CO2 storage. Based on these findings, a 20-50 g/L salinity range is recommended to maintain reservoir integrity and reduce the negative impacts of salinity on CO2 storage efficiency and storage. This study provides valuable insights for optimizing CO2 storage in DSAs, enhancing environmental sustainability, and enhancing mineral trapping through more targeted geochemical reactions and lower changes in rock mechanical strength.

The performance of carbon geo-sequestration is influenced by several parameters, such as the heterogeneity of the reservoir, the characteristics of the caprock, the wettability of the rock, and the salinity of the aquifer brine. Although many characteristics, like the formation geology, are fixed and cannot be altered, it is feasible to choose and manipulate other parameters in order to design an optimized storage programme such as the implementation of CO2 injection techniques, including continuous injection or water alternating CO2, which can significantly increase storage capacity and guarantee secure containment. Although WAG (water-alternating-gas) technology has been widely applied in several industrial sectors such as enhanced oil recovery (EOR) and CO2 geo-sequestration, the impact of the CO2-to-water ratio on the performance of CO2 geo-sequestration in heterogeneous formations has not been investigated. In this study, we have constructed a 3D heterogeneous reservoir model to simulate the injection of water alternating gas in deep reservoirs. We have tested several CO2-water ratios, specifically the 2:1, 1:1, and 1:2 ratios. Additionally, we have estimated the capacity of CO2 trapping, as well as the mobility and migration of CO2. Our findings indicate that injecting a low ratio of CO2 to water (specifically 1:2) resulted in a much better performance compared to situations with no water injection and high CO2-water ratios. The residual and solubility trappings were notably increased by 11% and 19%, respectively, but the presence of free mobile CO2 was reduced by 27%. Therefore, in the reservoir under investigation, the lower CO2-water ratio is recommended due to its improvement in CO2 storage capacity and containment security.

The Wyoming CarbonSAFE project is located at the Powder River Basin (PRB) in northeast Wyoming, which aims to safely store over 50 million metric tons of CO 2 for a period of 30 years at three stacked reservoirs including Lakota sandstone, Hulett sandstone, and Upper Minnelusa formation. Site-specific characterization data, including well logs, seismic data, core data, and field tests, are integrated into the dynamic model for initializing reservoir pressure and regional stress state and estimating petrophysical and rock mechanical properties. An integrated reservoir simulation and geomechanical modeling are then performed to estimate the well injectivity, storage capacity, surface displacement, integrity of reservoir and caprock, and fault stability. The presented workflow demonstrates how the stacked storage approach helps with large-scale geologic carbon sequestration within structurally complex reservoirs

As an important means of CO₂ geological storage leakage monitoring, resistivity monitoring technology is of great significance to the safety and stability of CCUS project. In order to study the electrical signal response rule of the evolution of CO₂ saturation in the reservoir, a joint core displacement experiment system of electrochemical impedance analysis and microfocus X-ray CT was designed and constructed to simulate the process of CO₂ displacement of brine in Berea sandstone cores under stratigraphic temperature and pressure conditions. The electrochemical impedance characteristics of the core-fluid system are analyzed by electrochemical impedance spectroscopy. The experimental results show that at lower temperature and pressure, it is more difficult for CO₂ to invade the pore space occupied by the brine in situ, resulting in drastic changes in CO₂ plane saturation along the displacement direction. With the increase of temperature and pressure, the CO₂ saturation curve becomes smoother and the migration and displacement front becomes even. The Cole equivalent circuit model is used to describe the conduction mode of AC electrical signals inside the core, and the electrochemical impedance characteristic analysis focusing on the high frequency region shows that the system impedance increases with the increase of CO₂ saturation, and decreases with the increase of scanning frequency. In addition, the changes of impedance characteristics in the electrochemical impedance spectroscopy not only reflect the pore structure characteristics of the core, but also reveal the evolution law of CO₂ saturation in the porous medium. With the increase of CO₂ saturation, the low pore space is gradually occupied by CO₂, and the residual brine connectivity of the pore space as a conductive component decreases. The decrease of the internal conductive circuit leads to the rapid increase of the impedance, which is consistent with the change of resistance and capacitance when fitting the Cole equivalent circuit model.

Abstract Supercritical ${\rm CO}_2$ injection and dissolution into deep brine aquifers allow its sequestration within geological formations. After injection, ${\rm CO}_{2}$ gas phase is buoyancy-driven over the denser aqueous brine, reaching an apparent gravitational stable distribution. However, ${\rm CO}_2$ dissolution in brine propels convection since the mixture is even denser than the underlying brine. This process still needs to be characterised comprehensively. Here, we investigate the irreversible mixing of dissolved ${\rm CO}_2$ in brine through laboratory-scale numerical experiments utilising the Hele-Shaw model (Letelier et al., J. Fluid Mech., vol. 864, 2019, pp. 746–767) and a fully miscible two-fluid system. In this scenario, mixing the less dense fluid – mimicking ${\rm CO}_{2}$ gas phase – with the heavier fluid – representing aqueous brine – catalyses cabbeling-powered convection. Our numerical simulations recover the laboratory results in porous media by Neufeld et al. (Geophys. Res. Lett., vol. 37, issue 22, 2010, L22404) and may explain the scaling law obtained by Backhaus et al. (Phys. Rev. Lett., vol. 106, issue 10, 2011, 104501) in Hele-Shaw cells. More remarkably, we show that the mass flux between the two analogue fluids, characterised by the Sherwood number $ {{Sh}}$, obeys the universal scaling law $ {{Sh}}\sim {{Ra}}\, \vartheta _{scalar}$, with $ {{Ra}}$ the Rayleigh number and $\vartheta _{scalar}$ the mean scalar dissipation rate. This paper sheds light on the fluid dynamics and solubility trapping in geological carbon sequestration.

Injecting greenhouse gas into deep underground reservoirs for permanent storage can inadvertently lead to fault reactivation, caprock fracturing and greenhouse gas leakage when the injection-induced stress exceeds the critical threshold. Extraction of pre-existing fluids at various stages of injection process, referred as pressure management, can mitigate associated risks and lessen environmental impact. However, identifying optimal pressure management strategies typically requires thousands of full-order simulations due to the need for function evaluations, making the process computationally prohibitive. This paper introduces a novel surrogate model-based reinforcement learning method for devising optimal pressure management strategies for geological CO2 sequestration efficiently. Our approach comprises two steps. Firstly, a surrogate model is developed through the embed to control method, which employs an encoder-transition-decoder structure to learn latent dynamics. Leveraging this proxy model, reinforcement learning is utilized to find an optimal strategy that maximizes economic benefits while satisfying various control constraints. The reinforcement learning agent receives the latent state space representation and immediate reward tailored for CO2 sequestration and choose real-time controls which are subject to predefined engineering constraints in order to maximize the long-term cumulative rewards. To demonstrate its effectiveness, this framework is applied to a compositional simulation model where CO2 is injected into saline aquifer. The results reveal that our surrogate model-based reinforcement learning approach significantly optimizes CO2 sequestration strategies, leading to notable economic gains compared to baseline scenarios.

Carbon dioxide (CO2) foams have emerged as a promising strategy for enhanced oil recovery (EOR), providing effective gas mobility control. However, challenges in maintaining subsurface stability and enabling surface-controlled collapse persist, and a comprehensive assessment of their CO2 storage potential remains unexplored. This study presents an innovative approach using switchable foams stabilized by a CO2-responsive surfactant, N-erucamidopropyl-N,N-dimethylamine (UC22AMPM). Through integrated laboratory experiments under simulated reservoir conditions, the reversible foaming/defoaming, in situ foam generation and transport in porous media, as well as CO2 storage capacity were systematically evaluated. The results reveal a unique reversible foam modulation mechanism driven by alternating CO2 and N2 exposure with CO2-induced foams displaying distinct pressure-dependent stability profiles. Microfluidic visualization technique demonstrates efficient in situ foam generation within porous media, further corroborated by core-flooding experiments revealing resistance factors of up to 14, underscoring their robust conformance control capability. Absorption experiments operating under simulated oil reservoir indicates a 22% increase in CO2 sequestration efficiency compared to traditional brine flooding. These findings provide a quantitative framework for harnessing the potential of CO2-responsive foams in both EOR operations and sustainable carbon sequestration.

No abstract available

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The increasing need to address climate change and ensure energy security has emphasized the importance of carbon capture, utilization, and storage (CCUS) technologies, particularly CO2-enhanced oil recovery (CO2-EOR), for achieving net-zero emissions. While CO2-EOR has demonstrated success in conventional reservoirs, its application in unconventional formations, such as the Bakken shale, presents challenges due to ultra-low permeability, complex fracture networks, and geological heterogeneity. Traditional numerical simulations are computationally intensive and often fail to adequately capture the complex dynamics of unconventional reservoirs. This study introduces a novel workflow that integrates compositional reservoir simulations with advanced deep learning (DL) architectures to predict CO2-EOR performance and storage potential in the Bakken formation. Key reservoir parameters such as porosity, permeability, and fluid viscosities are transformed into multi-dimensional input features to train and evaluate three DL architectures: Fully Connected Neural Networks (FCNN), Residual Neural Networks (ResNet), and Densely Connected Networks (DenseNet). These models predict oil saturation, CO2 saturation, and pressure distributions with high accuracy. ResNet consistently outperformed the other models, achieving the lowest Mean Absolute Error (MAE) values of 0.0115, 0.008, and 0.1471, and the highest coefficient of determination (R2) values of 0.9204, 0.9406, and 0.9969 for oil saturation, CO2 saturation, and pressure, respectively. The integration of compositional simulations with DL models addresses computational and geological uncertainties, providing a scalable framework for optimizing CO2 injection strategies, enhancing hydrocarbon recovery, and maximizing CO2 storage in unconventional reservoirs. This research contributes to advancing CCUS technologies and improving the economic and environmental outcomes of subsurface energy management.

The increasing global demand for energy continues to drive interest in efficient enhanced oil recovery (EOR) methods, particularly for challenging reservoirs containing extra-heavy crude oil. Traditional thermal recovery methods often prove economically and technically unsuitable for high-pressure, high-temperature (HPHT) environments. In this context, CO2-based miscible flooding has emerged as a favorable EOR technique due to its capacity to reduce interfacial tension and improve displacement efficiency. However, the high injection pressures required to achieve miscibility frequently exceed formation fracture gradients, making practical implementation difficult. To address this challenge, the objective of this study is to investigate the use of an environmentally friendly ionic liquid (IL), 1-methyl-3-octylimidazolium chloride ([MOIM]Cl), to reduce the minimum miscibility pressure (MMP) and first contact miscibility pressure (FCMP) in a CO2–extra-heavy oil system under elevated temperatures. Experimental investigations were conducted using the vanishing interfacial tension (VIT) technique, a proven approach for determining critical miscibility conditions. A crude oil sample with a density of 1.067 g/cm³ and viscosity of 9900 cP was selected to represent extra-heavy oil reservoirs. The sample was characterized through SARA analysis and TAN measurements to evaluate its compositional polarity and interaction potential with the IL. Interfacial tension (IFT) measurements were performed under varying pressure and temperature conditions at two targeted temperatures, 50 °C and 90 °C. The effect of incorporating 0.5 wt.% of [MOIM]Cl into the oil sample was evaluated through a comparison of the MMP and FCMP before and after IL addition. The findings showed that the addition of [MOIM]Cl had no beneficial impact on miscibility at 50 °C, with MMP and FCMP values increasing slightly from 1690 psi to 1749.7 psi and from 2705.8 psi to 2869.5 psi, respectively. However, at 90 °C, the inclusion of [MOIM]Cl resulted in a notable reduction in miscibility pressures. The MMP decreased from 2783.9 psi to 2351.7 psi (a 15.5% reduction), and the FCMP dropped from 4183.9 psi to 3756.1 psi (a 10.2% reduction). These results confirmed that the IL performs more effectively under elevated temperature conditions, particularly in systems containing polar and viscous crude oil with high asphaltene and aromatic content. This study highlights the novel application of a biodegradable and thermally stable IL for enhancing CO2 miscibility in extra-heavy oil systems, offering a promising and safer alternative for EOR and carbon storage in HPHT reservoirs.

CO2-enhanced oil recovery (CO2-EOR) with water-alternating-gas (WAG) injection offers the dual benefit of boosted oil production and CO2 storage, addressing both energy needs and climate goals. However, designing CO2-WAG schemes is challenging; maximizing oil recovery, CO2 storage, and economic returns (net present value, NPV) simultaneously under a limited simulation budget leads to conflicting trade-offs. We propose a novel closed-loop multi-objective framework that integrates high-fidelity reservoir simulation with stacking surrogate modeling and active learning for multi-objective CO2-WAG optimization. A high-diversity stacking ensemble surrogate is constructed to approximate the reservoir simulator. It fuses six heterogeneous models (gradient boosting, Gaussian process regression, polynomial ridge regression, k-nearest neighbors, generalized additive model, and radial basis SVR) via a ridge-regression meta-learner, with original control variables included to improve robustness. This ensemble surrogate significantly reduces per-evaluation cost while maintaining accuracy across the parameter space. During optimization, an NSGA-II genetic algorithm searches for Pareto-optimal CO2-WAG designs by varying key control parameters (water and CO2 injection rates, slug length, and project duration). Crucially, a decision-space diversity-controlled active learning scheme (DCAF) iteratively refines the surrogate: it filters candidate designs by distance to existing samples and selects the most informative points for high-fidelity simulation. This closed-loop cycle of “surrogate prediction → high-fidelity correction → model update” improves surrogate fidelity and drives convergence toward the true Pareto front. We validate the framework of the SPE5 benchmark reservoir under CO2-WAG conditions. Results show that the integrated “stacking + NSGA-II + DCAF” approach closely recovers the true tri-objective Pareto front (oil recovery, CO2 storage, NPV) while greatly reducing the number of expensive simulator runs. The method’s novelty lies in combining diverse stacking ensembles, NSGA-II, and active learning into a unified CO2-EOR optimization workflow. It provides practical guidance for economically aware, low-carbon reservoir management, demonstrating a data-efficient paradigm for coordinated production, storage, and value optimization in CO2-WAG EOR.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 25000, “Integrated Well-Network-Design Mode for CO2 EOR and Storage and Its Application in L Reservoir,” by Zangyuan Wu, PetroChina, CNPC, and China University of Petroleum; Yongliang Tang, PetroChina and CNPC; and Liming Lian, CNPC, et al. The paper has not been peer-reviewed. Copyright 2025 International Petroleum Technology Conference. This paper addresses the challenge of adjusting late-stage production in waterflooded reservoirs and proposes an integrated well-network-design mode for CO2 enhanced oil recovery (EOR) and storage. The well network is designed according to the full life cycle of carbon capture, use, and storage (CCUS), meeting the requirements of both CO2 EOR and storage phases. The L reservoir structure is in a zone consisting of a series of long-axis anticlines trending nearly east/west. The structure includes multiple development blocks on the plane, is intact overall, and has good sealing conditions. The L oil reservoir is divided vertically into two sublayers, L-1 and L-2. Based on the statistical analysis of core-sampling experimental data, the L-1 sublayer has an average porosity of 16.2% and a permeability of 39.3 md, classifying it as a medium-porosity, low-permeability reservoir. The L-2 sublayer has an average porosity of 19.5% and a permeability of 193.4 md, classifying it as a medium-porosity, medium-permeability reservoir. The reservoir properties of L-2 are significantly better than those of L-1. The crude oil from the L reservoir has good properties, characterized by low viscosity, low pour point, medium-to-low sulfur content, high wax content, and medium-to-high asphaltene content. The conditions of the L reservoir make it well-suited for CO2 EOR. At the start of CO2 injection, because of the strong solubility of crude oil, CO2 can dissolve into the oil quickly upon pressurization. Therefore, the gas/oil ratio (GOR), expansion coefficient, and saturation pressure increase gradually. The dissolution of CO2 into the crude oil and the extraction of CO2 from the crude oil lead to a gradual decrease in viscosity. The expansion coefficient increases from 1.0000 to 1.3978, an increase of 40%, and the viscosity of the crude oil decreases from 3.617 to 1.052 mPa·s, a reduction of 70%. This indicates that, after CO2 is injected into the reservoir, it can achieve effective expansion and viscosity reduction. To characterize the properties and water-content differences of the L-1 and L-2 sublayers, suitable cores were selected based on measured porosity and permeability data. Special long-core-displacement experiments were conducted, including continuous gas driving after waterflooding, water-alternating-gas (WAG), cyclic gas injection, and CO2 + hydrocarbon-slug-displacement experiments. The oil-displacement efficiency of miscible CO2 injection exceeds 80% in all cases, and different gas-injection methods after waterflooding can enhance oil-displacement efficiency significantly. Both cyclic CO2 injection and WAG after waterflooding achieve efficiencies greater than 90%, and both can control the rise in the GOR effectively; continuous CO2 injection without profile modification and CO2 + hydrocarbon-slug injection, where the hydrocarbon is a nonmiscible component, affect the oil-displacement efficiency of these two injection methods.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 221978, “Development of Fast Predictive Models for CO2 Enhanced Oil Recovery and Storage in Mature Oil Fields,” by Yessica Peralta, Ajay Ganesh, and Gonzalo Zambrano, SPE, University of Alberta, et al. The paper has not been peer-reviewed. Reservoir modeling tools have played a significant role in designing subsurface fluid-injection methods such as CO2 enhanced oil recovery (EOR). However, these models are computationally expensive, requiring extensive geological and engineering data that often are not available in the early phases of carbon use and storage projects. This work presents the development of fast predictive models and optimization methodologies to evaluate CO2 EOR and storage operations quickly in mature oil fields. Model Description. The Weyburn oilfield is in southern Saskatchewan, Canada. Weyburn oil reserves are within a thin zone of fractured carbonates (maximum thickness of 30 m) deposited in a shallow carbonate shelf environment at a depth of 1350–1450 m. The reservoir consists of two main units, the upper Marly dolostone (thickness ranging from 0 to 10 m) and the lower vuggy limestone (thickness ranging from 0 to 20 m). Oil production began in 1956. CO2 miscible-flooding EOR was initiated in 2000, alternating with water in some wells to improve oil-recovery efficiency and to store CO2 for the long term. The Weyburn-Midale CO2 EOR model in this work is a subarea of the Phase 1A monitoring and storage project. It was developed by using a commercial compositional reservoir simulator. History matching was performed by using 216 well histories (producers and injectors) from April 1964 to the end of 2006. Numerical-Grid Construction. The total model dimensions are 7000, 7800, and 30 m, corresponding to the model width, length, and thickness, respectively. The number of gridblocks is 141×280×27, conforming to 1,065,960 total gridblocks. The reservoir thickness is approximately 30 m. The 27 vertical layers of the Weyburn-Midale CO2 EOR grid model are distributed as eight layers of marly dolostone (upper layers), four layers of vuggy intershoal, seven layers of vuggy shoal, and eight layers of vuggy lower shoal. Reservoir and Fluid Properties. The Weyburn-Midale reservoir is an anisotropic heterogeneous fractured reservoir. The marly unit is chalky intertidal dolostone with some interbeds of limestone with porosity ranging from 16 to 38%. The matrix permeability ranges from 1 to more than 100 md. The vuggy zone constitutes a heterogeneous subtidal limestone with varied diagenetic and depositional environments, resulting in porosity values from 3 to 18%. The matrix permeability varies from less than 0.01 to more than 500 md, where fractures control the direction and the magnitude of permeability anisotropy. The reservoir features an initial temperature of 63°C and a reference pressure of 15.2 MPa at a depth of 1440 m. The original oil and water in place are 40.16 MRm3 and 21.67 MRm3, respectively. The model’s total pore volume is 61.29 MRm3, with an initial fluids saturation of 65% oil and 35% water.

The Farnsworth Unit in northern Texas is a field site for studying geologic carbon storage during enhanced oil recovery (EOR) using CO2. Microseismic monitoring is essential for risk assessment by detecting fluid leakage and fractures. We analyzed borehole microseismic data acquired during CO2 injection and migration, including data denoising, event detection, event location, magnitude estimation, moment tensor inversion, and stress field inversion. We detected and located two shallow clusters, which occurred during increasing injection pressure. The two shallow clusters were also featured by large b values and tensile cracking moment tensors that are obtained based on a newly developed moment tensor inversion method using single-borehole data. The inverted stress fields at the two clusters showed large deviations from the regional stress field. The results provide evidence for microseismic responses to CO2/fluid injection and migration.

Both laboratory tests and pilot wells have demonstrated the significant potential of CO2 as an enhanced oil recovery (EOR) medium. Due to the weak pressure conduction and mass transfer of the CO2-oil system, multiple zones are generated between the injection well and production well in ultra-low permeability reservoirs. This work aims to explore the characteristics of these multiple zones and the mechanisms of CO2-EOR by combining experimental results, core-scale analysis, and field-scale simulation. Long-core CO2 displacement experiments were conducted under different miscibility pressures, with production gas assayed using gas chromatography. The core-scale simulation was aligned with the experimental results, defining four CO2 fronts to distinguish different zones based on pressure, interfacial tension, and CO2 concentration along the long core. The distribution of five zones was upscaled to the field-scale model after pilot well history matching. The final step involved evaluating the miscible zone range value, CO2 injection utilization factor, oil recovery, and CO2 storage efficiency during the CO2 injection process. Results show that the boundary between the original oil zone and the oil transition zone exists at the CO2 component front, where the CO2 concentration is zero. Additionally, the location of the CO2 component front does not overlap with the contact interface of CO2-crude oil, meaning that the dissolution effect of CO2 in the oil transition zone results in the CO2 component front moving farther. Besides, when the formation pressure is higher than the minimum miscibility pressure (MMP), the distance between the CO2-effective phase front and the CO2-effective component front further expands as the pressure increases, enlarging the miscible zone range. The pressure accumulates around the injection well because of slow pressure conduction. When the average formation pressure reaches 1.1 MMP, the miscible zone range is enlarged by 2.7% higher than that of the near miscible flooding (0.92 MMP), leading to a higher rate of oil recovery by 8.6% and a utilization factor of CO2 by 0.14t/t. It is for the first time that the range of five zones and the characteristics of four CO2 fronts migration is assessed, furnishing an in-depth understanding of the complicated mechanisms and phase behavior in CO2 EOR in the ultra-low permeability oil reservoir. This work contributes to providing significant information for designing an economic and environmental CO2 flooding strategy and is significant in the improvement of oil recovery and the reduction of CO2 emission.

CO2-EOR technology for low-permeability tight oil and gas reservoir is in the ascendant, and CO2-EOR technology for old oilfields has not been paid enough attention, but the implementation scale has great potential, and the expected effect and implementation conditions are good. The feasibility of CO2-EOR technology in the ultra-high water cut stage of high CO2 content, near saturation pressure and edge-bottom water reservoir was studied theoretically, and the field implementation effect was tracked and evaluated. Via petrophysics, reservoir engineering, and site case analysis, a relatively comprehensive reservoir numerical model was developed, clarifying the impact of periodic gas injection volume, gas injection rate, soak time and liquid production rate on the production effect of CO2 huff and puff were clarified. The key injection-production parameters of CO2 huff and puff test wells were designed, and the feasibility study progress of CO2-EOR in near-saturated edge-bottom water reservoirs with high CO2 content was summarized. The theoretical research shows that the change rules of gas-water dual-drive, CO2 water control and oil increase in the process of CO2 huff and puff in high CO2 near-saturated edge and bottom water reservoirs, and reveals the synergistic mechanism of CO2 huff and puff to suppress water and increase energy. The tracking evaluation shows that the sweep condition of CO2 after huff and puff in the test well is complex, the storage ratio is in the range of 40%-70%, the stage oil increase is in the range of 700t-3000t, and the optimized oil increase and oil change rate can reach 2.7t/t. Based on the comprehensive theory and practice, it is considered that CO2-EOR has good potential for high CO2 near-saturated edge and bottom water reservoirs under fine control. This study has guiding and reference significance for CO2-EOR technology and application in similar oilfields at home and abroad.

Presented on Thursday 18 May: Session 29 This study evaluates carbon dioxide enhanced oil recovery (CO2 EOR) for enhanced oil recovery (EOR), enhanced gas recovery (EGR) and carbon capture and storage (CCS) purposes in the mature Mereenie Oil and Gas Field (‘Mereenie’). Mereenie consists of a rim oil and gas cap reservoir with low aquifer activity. We evaluate the microscopic and macroscopic displacement efficiencies of CO2 EOR techniques after determining the minimum miscibility pressure of the CO2 and reservoir oil system. Investigations on EOR, EGR and CCS are then conducted on a sector model containing the main pay zones. The CO2 flood, water alternating gas (CO2 WAG) and Huff ‘n’ Puff methods are evaluated within three strategies: unstructured well placement, five-spot pattern configuration and gravity-assisted flood. The sector model shows performance of an immiscible process in oil and gas recovery and CO2 storage potential. The CO2 flood is efficient in oil recovery but less efficient in CO2 utilisation, making it a good option for a half oil recovery–half CO2 storage objective. The CO2 Huff ‘n’ Puff is more efficient for oil recovery at early stages of operation, and also very efficient for gas recovery. The CO2 Huff ‘n’ Puff technique is not a good option for the CO2 storage objective. The CO2 WAG could be a good technique for oil recovery and CO2 storage with proper CO2 slug size and WAG ratio. The five-spot pattern configuration enhances sweep efficiency. The gravity-assisted flood strategy can be appropriate for the rim oil reservoir with gas cap in Mereenie. To access the Oral Presentation click the link on the right. To read the full paper click here

This study evaluates carbon dioxide enhanced oil recovery (CO2 EOR) for enhanced oil recovery (EOR), enhanced gas recovery (EGR) and carbon capture and storage (CCS) purposes in the mature Mereenie Oil and Gas Field (‘Mereenie’). Mereenie consists of a rim oil and gas cap reservoir with low aquifer activity. We evaluate the microscopic and macroscopic displacement efficiencies of CO2 EOR techniques after determining the minimum miscibility pressure of the CO2 and reservoir oil system. Investigations on EOR, EGR and CCS are then conducted on a sector model containing the main pay zones. The CO2 flood, water alternating gas (CO2 WAG) and Huff ‘n’ Puff methods are evaluated within three strategies: unstructured well placement, five-spot pattern configuration and gravity-assisted flood. The sector model shows performance of an immiscible process in oil and gas recovery and CO2 storage potential. The CO2 flood is efficient in oil recovery but less efficient in CO2 utilisation, making it a good option for a half oil recovery–half CO2 storage objective. The CO2 Huff ‘n’ Puff is more efficient for oil recovery at early stages of operation, and also very efficient for gas recovery. The CO2 Huff ‘n’ Puff technique is not a good option for the CO2 storage objective. The CO2 WAG could be a good technique for oil recovery and CO2 storage with proper CO2 slug size and WAG ratio. The five-spot pattern configuration enhances sweep efficiency. The gravity-assisted flood strategy can be appropriate for the rim oil reservoir with gas cap in Mereenie.

For the purpose of greenhouse gas control and environment protection, CO2 emission reduction has become a hot spot in global research. CO2-EOR and geological storage are widely regarded as one of the most economical and promising emission reduction measures. In this paper, the 3D embedded discrete fracture model (EDFM) is built to simulate the interfracture CO2 flooding and geological storage process in fractured reservoirs. This model can deal with the complex geological conditions of three-dimensional arbitrary inclined fracture networks, significantly improve the calculation efficiency, and accurately evaluate the CO2-EOR process of real reservoirs. The obtained CO2 reserves and saturation distribution can provide key technical parameters for field operations.

Addressing climate change urgently requires effective carbon capture and storage (CCS) strategies to lower atmospheric carbon dioxide (CO2) levels. Depleted oil and gas reservoirs and saline aquifers are promising for CO2 geological sequestration due to their significant storage capacities. Furthermore, CO2 injection for Enhanced Oil Recovery (EOR) is a potential storage option for CO2 when CO2 flow back is controlled. Therefore, this study provides a techno-economic analysis to evaluate the feasibility, efficiency, and economic analysis of these different geological storage options for CO2 storage. The economic evaluations were conducted in compliance with Section 45Q tax credits for financial viability. The analysis employs a multidisciplinary methodology combining geological assessments, engineering principles, and economic models. It focuses on the long-term impact of injecting CO2. Additionally, it evaluates supercritical CO2 behavior to estimate potential trapping mechanisms and identify factors affecting sequestration efficiency and safety. Economic analysis is central to this study, detailing the costs associated with CO2 capture, compression, transportation, injection, and monitoring. The study also considers the influence of policies, regulations, and market conditions on CCS project economics, identifying incentives and barriers. The findings of this study affirm the potential of depleted oil and gas reservoirs and saline aquifers as viable CO2 storage solutions, offering a nuanced understanding of their role in global carbon mitigation efforts. The results show the economic superiority of the depleted oil and gas reservoirs in storing CO2 if the storage capacity is ignored (i.e., if all storing options are capable of storing the desired CO2 — 1 MM metric tons in this study). The results highlight that storing CO2 in depleted oil and gas reservoirs exhibits the highest financial viability, particularly when used in conjunction with Direct Air Capture (DAC) technologies. These options demonstrate the greatest Net Present Values (NPVs), making them attractive for large-scale CO2 storage projects. Compliant DAC facilities, particularly those utilizing depleted oil and gas reservoirs, achieve NPVs upwards of $27 million, underscoring their economic superiority. While saline aquifers and EOR present viable options due to higher storing capacity, their financial performance is generally lower compared to depleted oil and gas reservoirs if uniform stored volume is considered. The study also notes the significant cost variations influenced by factors such as CO2 capture, transportation, and storage technologies, alongside the availability of financial incentives. By outlining the challenges and opportunities, the study provides essential insights for stakeholders in CCS projects, suggesting a pathway through the complexities of CO2 sequestration towards sustainable climate action. Compliance with regulatory standards, particularly the Section 45Q tax credits, is emphasized as crucial for achieving positive financial outcomes and ensuring the success of CCS initiatives.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 216683, “Large-Scale, High-Throughput Sensitivity Analysis of CO2 Minimum Miscibility Pressure To Optimize Gas-Injection EOR Processes,” by Ali Abedini, SPE, ZhenBang Qi, SPE, and Thomas de Haas, SPE, Interface Fluidics, et al. The paper has not been peer reviewed. Performance of CO2 injection relies on accurate CO2 minimum miscibility pressure (MMP) and miscibility data at reservoir conditions. A slim tube is the most-reliable tool to measure MMP under different miscibility mechanisms; however, it is very time- and capital-intensive, making it impossible to provide high-throughput data to assess the effect of other gases. Rising-bubble apparatus and vanishing-interfacial-tension techniques are cheaper and easier to run, but these methods are unable to capture different miscibility mechanisms fully. In the case study presented in the complete paper, the authors present a highly efficient microfluidic platform to measure, in a faster and easier manner, high-quality MMP data of CO2 with various impurities significantly. Conducting miscibility tests at high pressure or high temperature with live oil samples and real gas mixtures requires a platform capable of handling complex fluid systems at reservoir conditions. An advanced microfluidic system was used to perform a large set of miscibility/MMP tests to investigate the role of different impurities on the MMP of pure CO2 with an oil sample from a depleted reservoir in Alberta. The results reported demonstrate the capabilities of the new microfluidic approach to provide fast and accurate high-volume miscibility and MMP data for a wide range of gas compositions unobtainable by conventional methods. The portable microfluidic platform integrates fluid-control, microfluidic, and imaging systems, enabling performance of a series of miscibility and MMP measurements (Fig. 1a). The platform is equipped with three high-pressure pumps to control gas injection, oil injection, and backpressure. The gas sample, oil sample, and effluent are stored in sample bottles heated with a heating jacket and connected to the pumps. The valves and tubing are placed in a valve box that heats up internally. The manifold is the holder for the microfluidic chip and consists of bottom and top pieces that sandwich the chip. The bottom of the manifold is controlled by a hydraulic pump. The time-lapse imaging is performed using a microscope equipped with a high-resolution camera. Fig. 1b shows the microfluidic chip and the porous media design. The serpentine porous media, with a total length of 57 cm, contains circular pillars to promote multiple contacts in the system. Table 1 of the complete paper contains the list of the gases used in this study. The composition of the recycled gas includes approximately 86% CO2, approximately 7.7% methane, and other impurities. To validate the accuracy of the microfluidic MMP, the data were compared with the MMP data obtained with the slim tube. The measurements were conducted with pure CO2 and a mix of CO2 with recycled gas. While the tests were not performed at exactly the same conditions and in the same time frame, the results showed that the microfluidic MMP data were in good agreement with those of the slim-tube tests.​​​​

No abstract available

Abstract This study investigates the possibility of carbon dioxide (CO2) storage and enhanced oil recovery (EOR) in the Barail shale of the Assam Arakan Basin, India. Drill cuttings and core samples are collected from depths ranging from 2,410 to 4,424 m and are examined in a laboratory. The research focuses on parameters like rock composition, porosity, permeability, surface area, pressure, reservoir fluid volume, and caprock integrity to determine the shale’s long-term CO2 storage capacity. The findings highlight the impact of surface area, depth, and mineralogy on storage capacity. The shale exhibits 8.8% porosity, 5.40% clay, 67.58% quartz and feldspar, and 17% carbonate along with an average total organic carbon (TOC) of 0.06 wt% to 1.42 wt% also identified the average pore volume ranges from 0.004 cc/g to 0.0026 cc/g by CO2 analysis and N2 gas. High-pressure adsorption isotherms for methane (CH4) and CO2 were analyzed to assess gas storage capabilities. The study primarily aims to understand factors affecting CH4 and CO2 sorption capacities, revealing that the shale exhibits a greater sorption capacity for CO2 compared to methane. This study serves as a benchmark for future field-based CO2 geosequestration work in the basin or in geologically similar basins worldwide.

CO2 is the main solvent used in enhanced oil recovery (EOR). However, its low density and viscosity compared to oil cause a decrease in sweep efficiency. Recently, dimethyl ether (DME), which is more efficient than CO2, has been introduced into the process. DME improves oil recovery by reducing minimum miscible pressure (MMP), interfacial tension (IFT), and oil viscosity. Since DME is an expensive solvent, price reduction and appropriate injection scenarios are needed for economic feasibility. In this study, a compositional model was developed to inject DME with impure CO2 streams, where the CO2 was derived from one of these three purification methods: dehydration, double flash, and distillation. It was assumed that such a mixed solvent was injected into a heterogeneous reservoir where gravity override was maximized. As a result, lower oil recovery is achieved for the higher impurity content of the CO2 stream, lower DME content, and more heterogeneous reservoir. When a high-purity CO2 stream is used, the change in oil recovery according to DME content and heterogeneity of the reservoir is increased. When the lowest-purity CO2 stream is used, the net present value (NPV) is the highest. For a homogeneous reservoir, the NPV is highest for all impure CO2 streams. This optimization indicates a greater impact on revenue from reduced CO2 purchase cost than on profit loss due to reduced oil recovery by impurities. Additional benefits can be expected when considering solvent reuse and carbon capture and storage (CCS) credits.

The synergistic development of enhanced oil recovery (EOR) and Carbon Capture, Utilization, and Storage (CCUS) by water-alternating-gas (WAG) technology in fractured tight reservoirs was researched. As a key component of CCUS, continuous CO2 injection (CCI) faces inherent limitations in tight reservoirs with well-developed natural fractures, including mitigating gas breakthrough and poor sweep efficiency. While WAG injection improves mobility control, the multiphase flow mechanisms and CO2-water-oil-rock interactions in fractured systems remain insufficiently understood. The CCI and WAG injection experiments were conducted by utilizing natural tight core samples from the Ordos Basin with core artificial manufracturing technology and high-precision nuclear magnetic resonance (NMR) monitoring technology, and the in-situ characterization of dynamic fluid distributions were characterized. Experimental results demonstrate that compared to continuous flooding, CO2-WAG increases flow resistance by 3-8 times while enhancing oil recovery by 5.1%-9.0% and storage efficiency by 4.3%-5.6%. The optimal segment plug ratios of 1:1 was identified due to the highest comprehensive CO2 utilization-storage factor. Furthermore, for the fractured core with 50% fracture penetration ratio, compared to the no fractured cores, oil recovery was decrease by 16.5 % and CO2 storage efficiency was reduced by 7.4 %, Further analysis integrated with NMR imaging results, it revealed that the injected water during CO2-WAG can preferentially occupy the dominant flow pathways or fractures, thereby suppressing gas breakthrough through the Jamin effects. Integrated with component numerical simulation results, it was identified that substantial flow resistance was established by high-water-content slugs within porous media, while high-gas-content slugs effectively facilitate CO2 wave propagation and diffusion effects. These findings demonstrate strong agreement with core-scale experimental observations. The high-precision NMR scanning and evaluation method and component numerical simulation proposed in this paper provide theoretical support for CO2-WAG enhanced oil recovery and storage synergistic development in tight reservoirs, and the application of CCUS in unconventional reservoirs was promoted.

In geological CO2 storage, designing the optimal well control strategy for CO2 injection to maximize CO2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO2 storage operation.

Climate change policies are driving the oil and gas industry to explore CO2 injection for carbon dioxide storage in reservoirs. In the United States, a substantial portion of oil production relies on CO2-enhanced-oil-recovery (CO2-EOR), demonstrating a growing interest in using CO2 to address various production challenges like condensate mitigation, pressure maintenance, and enhancing productivity in tight reservoirs. CO2 injection introduces gases like natural gas and N2, either pre-existing or as impurities in the injected CO2 gas. These gases alter the interaction of CO2 with the oil or condensate in the reservoir, with interfacial tension playing a crucial role in governing miscibility, mobilization, and phase distribution. Effectively implementing gas injection techniques requires a precise understanding of interfacial tension between injected gases and reservoir fluid under reservoir conditions. This study aims to evaluate the effects of oil composition, gas composition, pressure, and, temperature on interfacial tension and provides a comprehensive understanding of IFT dynamics for CO2-EOR implementation. The study utilizes the pendant drop analysis technique to assess the impact of pressure, temperature, and gas composition on crude oil and condensate interfacial tension. Measurements span a range of temperature (30–85 oC), pressure (0.7–7 MPa), and mixture composition (CO2: N2 ratios of 90:10 and 10:90), including pure CO2 and N2 with crude oil and condensate. Accurate measurement of interfacial tension incorporates changes in oil and gas density as functions of pressure and temperature. Results show that interfacial tension is significantly influenced by pressure, temperature, and gas composition. It decreases with increasing pressure at constant temperature and gas composition for both crude oil and condensate. While temperature-induced reductions in interfacial tension occur, they are overshadowed by the more pronounced effect of pressure. Gas composition significantly affects system interfacial tension; an increase in CO2 mole fraction decreases it, while an increase in N2 mole fraction causes an upturn. Changes in CO2 mole fraction result in concave downward trends, whereas changes in N2 mole fraction lead to concave upward trends. These findings are crucial for understanding the interaction of injected gas with reservoir fluid and can be applied to model interfacial tension with hydrocarbon fluid. This study offers an in-depth understanding of interfacial tension dynamics in CO2-EOR, a process that is increasingly attracting global attention for CO2 utilization. The research stands out for its innovative experimentation and detailed analysis, which focus on evaluating the impact of individual parameters crucial for modeling. Additionally, it sheds light on the combined effects of these parameters, which are essential for practical field applications. This knowledge is instrumental in designing processes such as CO2-EOR and condensate banking, incorporating the effects of pressure, temperature, and gas composition at the reservoir scale.

CO2-enhanced oil recovery (EOR) is a key technology to improve oil recovery rates and support carbon capture, utilization, and storage (CCUS). Injecting CO2 into reservoirs reduces crude oil viscosity, enhancing its mobility. A critical factor in CO2-EOR is determining the Minimum Miscibility Pressure (MMP). This study aims to construct an MMP prediction model for pure and impure CO2-EOR based on an improved eXtreme Gradient Boosting (XGBoost) algorithm, introducing the critical temperature of the injection gas (Tcm) as a new research variable to explore its impact on MMP. The data used in this study comprises 218 experimental datasets, totaling 2,398 samples, covering both pure and impure CO2-EOR scenarios. Before model construction, important features related to MMP were identified by combining reservoir physical theory with Pearson correlation analysis, and dimensionality reduction was performed using principal component analysis to eliminate redundant information. To optimize the hyperparameters of XGBoost, this study introduced the Particle Swarm Optimization (PSO) algorithm to ensure optimal model parameter configuration. Additionally, Shapley Additive Explanations (SHAP) analysis was employed to evaluate the model’s interpretability, resulting in a CO2-MMP prediction model with good explanatory capability. The results indicate that the proposed method achieved an RMSE of 0.2347 and an R2 of 0.9991 for the training set, with an RMSE of 1.0303 and an R2 of 0.9845 for the testing set, outperforming traditional MMP prediction models in various performance metrics. The proposed methodology enables a transparent, efficient, and generalizable approach to MMP prediction, offering valuable insights for CO2-EOR strategy design and supporting more cost-effective and data-driven reservoir development.

The flow mechanism of CO2 flooding serves as the theoretical foundation for examining the synergic integration of oil recovery and CO2 storage. Immiscible CO2 flooding has attracted considerable research attention due to its simplicity and cost-efficiency. However, minimal studies are available regarding the flow characteristics and EOR mechanism of immiscible CO2 flooding in in-situ temperature-pressure coupling conditions at the pore scale. Therefore, this study employed a modified high-temperature, high-pressure microfluidic system to simulate the in-situ CO2 and water injection processes in a combined temperature-pressure environment and analyze the multiphase flow characteristics in the pores. The injection rate, displacement pressure difference, displacement efficiency, and residual oil distribution were quantitatively analyzed at different pressures. The results indicated higher residual oil clustering after water flooding at the same injection rate. CO2 flooding significantly reduced residual oil clustering and enhanced the oil flooding effect. The multiphase flow dynamics, type of remaining oil in different injection conditions, and flow characteristics of immiscible CO2 flooding were determined. A higher confining pressure interrupted the CO2 flow, which destabilized the displacement front increased the recovery efficiency by 12.9%. Furthermore, a higher injection rate and displacement pressure increased the recovery efficiency by 24.9% and 6.1%, respectively.

Carbon dioxide (CO2) injection has gained popularity in the petroleum industry as a dual-purpose method for enhanced oil recovery (EOR) and long-term carbon sequestration. However, assessing the performance of CO2 EOR and its storage potential across large-scale fields is a complex task, primarily due to the heterogeneous geological characteristics of reservoirs and the dynamic behavior of injected CO2. Traditional methods for evaluating CO2 injection often rely on manual interpretations or computationally expensive reservoir simulations, both of which can be biased, time-intensive, and less effective for fieldwide analyses involving extensive data sets. In this study, a data mining-driven methodology was developed and applied to one of the most prominent CO2 injection projects in the world. More than 2,000 wells with decades-long production histories were analyzed using advanced statistical and geostatistical approaches, including spatial and temporal normalization of production data. By correlating key production metrics with geological features inferred from the data, fracture-dominated and matrix-dominated regions within the field were identified. The analysis further highlighted zones with differing CO2 injection efficiency and oil displacement behavior, providing a comprehensive understanding of reservoir performance in terms of oil recovery and CO2 sequestration. A critical aspect of the methodology involved combining multiple production metrics—such as gas/oil ratio (GOR), water cut (WCT), time to peak production, and CO2 breakthrough patterns—using Z-score-based normalization across both spatial and temporal domains. This approach enabled localized trend interpretation while maintaining consistency with physical reservoir behavior. Zones where CO2 injection was successful in both enhancing oil recovery and sequestering carbon were differentiated from areas where CO2 rapidly broke through without effective oil displacement, primarily due to fracture orientations and density (less vertically oriented fractures or matrix system dominated reservoir sections). Additionally, regions dominated by vertical fractures, which contributed to long-term CO2 storage, were identified. The results of this work provide valuable insights for optimizing CO2 injection strategies and improving sweep efficiency, ultimately aiding in better decision-making for both enhanced recovery and greenhouse gas sequestration. This novel approach bridges the gap between data-driven analysis and traditional reservoir engineering principles, offering a scalable framework for CO2 EOR operations in fields with complex geologies.

Numerical simulation of CO2-enhanced oil recovery (CO2-EOR) critically advances hydrocarbon field development by quantifying multiphase saturation dynamics during CO2-driven displacement. This study establishes a cylindrically configured 1D triple-phase mathematical model integrating Darcy's law and mass conservation principles, employing an implicit pressure-explicit saturation (IMPES) finite-difference scheme to resolve spatiotemporal evolution of aqueous, oleic, and gaseous phase saturations. Systematic incorporation of chemical reaction kinetics, viscosity-pressure coupling, and dynamic relative permeability effects yields a novel computational framework for immiscible displacement analysis. Simulations reveal two governing mechanisms: 1) CO2-saturated fluid/rock interactions induce pore-throat dilation, amplifying effective flooding radii; 2) Wellbore-formation pressure differentials (ΔP) dictate CO2 plume propagation, where elevated ΔP expands repulsion radii and oil displacement annulus thickness. Paradoxically, increased reservoir porosity reduces annular confinement while diminishing displacement efficiency despite enhanced volumetric throughput, with simulations confirming persistent oil-rich annuli characteristic of non-miscible regimes. These findings provide actionable guidelines for optimizing CO2-EOR injectivity parameters and ensuring long-term carbon sequestration integrity in heterogeneous formations, bridging theoretical modeling with field-scale implementation strategies.

Due to concerns over rising emissions of carbon dioxide (CO2) from fossil fuel utilization, there has been a strong emphasis on the development of a safe, economical, practical method of carbon capture utilization and storage (CCUS). One way to reduce these CO2 emissions is underground geological sequestration in depleted oil fields or exhausted reservoirs. CO2 injection into oil reservoirs is an established technology, these reservoirs not only offer the potential for high storage of CO2 but this process could also target a large amount of oil and gas recovery through a technique called enhanced oil recovery (EOR). The main objective of this research was to evaluate the storage potential of CO2 in the depleted oil field while also investigating the effect of CO2 injection on reservoir pressure maintenance, and additional oil and gas recovery, in the same field. This paper presented the model of CO2 flooding based on the CO2 displacement mechanism with different scenarios of natural depletion, CO2 injection, and water injection simulated by the ECLIPSE 300 reservoir simulator, and the results of different scenarios were compared. Results of this study showed the site selected for CO2 injection has the potential to store more than 9 billion cubic feet (BCF) of CO2 in each case and witnessed improved gas recovery, while also having a major effect on reservoir pressure maintenance where pressure increased from 2120 psi to 6584 psi. The finding of this work ought to help in preparing for future improvement in underground geological sequestration of CO2 in depleted fields with the same field specifications.

Under the policy background and advocacy of carbon capture, utilization, and storage (CCUS), CO 2 -EOR has become a promising direction in the shale oil reservoir industry. The multi-scale pore structure distribution and fracture structure lead to complex multiphase fl ow, comprehensively considering multiple mechanisms is crucial for development and CO 2 storage in fractured shale reservoirs. In this paper, a multi-mechanism coupled model is developed by MATLAB. Compared to the traditional Eclipse 300 and MATLAB Reservoir Simulation Toolbox (MRST), this model considers the impact of pore structure on fl uid phase behavior by the modi fi ed Peng e Robinson equation of state (PR-EOS), and the effect simultaneously radiate to Maxwell e Stefan (M e S) diffusion, stress sensitivity, the nano-con fi nement (N-C) effect. Moreover, a modi fi ed embedded discrete fracture model (EDFM) is used to model the complex fractures, which optimizes connection types and half-transmissibility calculation approaches between non-neighboring connections (NNCs). The full implicit equation adopts the fi nite volume method (FVM) and Newton e Raphson iteration for discretization and solution. The model veri fi cation with the Eclipse 300 and MRST is satisfactory. The results show that the interaction between the mechanisms signi fi - cantly affects the production performance and storage characteristics. The effect of molecular diffusion may be overestimated in oil-dominated (liquid-dominated) shale reservoirs. The well spacing and injection gas rate are the most crucial factors affecting the production by sensitivity analysis. Moreover, the potential gas invasion risk is mentioned. This model provides a reliable theoretical basis for CO 2 -EOR and sequestration in shale oil reservoirs.

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 224150, “A Machine-Learning-Based Co-Optimization Framework Improves CO2 Sequestration and Oil Recovery,” by Kassem Alokla, SPE, James Omeke, SPE, and Esuru Rita Okoroafor, SPE, Texas A&M University, et al. The paper has not been peer reviewed. This work combines CO2-enhanced oil recovery (EOR) methods with subsurface containment strategies to permanently store CO2 while simultaneously increasing cost-effective oil production from reservoirs. The study develops a novel workflow with multiobjective optimization techniques to assess the integration of pressure-management methodologies for permanent geological CO2 storage in saline aquifers. Reservoir Model Description. A homogeneous reservoir model, representative of typical Gulf of Mexico formations, was constructed using a nonisothermal modeling code for the purpose of the project. The model features a shale layer separating an oil reservoir from an aquifer, allowing the assessment of simultaneous CO2-EOR and CO2 sequestration. The model was designed under a compositional multicomponent system using the EOS-PVT E300 simulator. Pure CO2 was selected as the injection fluid for the simulation. The relative permeability functions for water/oil and gas/oil systems were calculated based on Stone’s approach to define the related coefficients. Simulation Approach. The static model consisted of 42,966 grid cells with 36, 62, and 21 grids in the I, J, and K directions, respectively. For equilibrium initialization, this model used a datum depth of 6,000 ft and a pressure of 3,375 psi. For the base case, the average permeability and porosity for the aquifer and reservoir were 106 md and 17%, respectively. Permeability was considered as a function of porosity. The shale formation was assumed to be completely impermeable, and the anisotropy ratio of modeled permeability in both reservoir and aquifer was 0.1. The base case was developed to test the performance of the system and investigate the ranges of the parameters needed for the optimization process. For that purpose, the wells considered for the aquifer were a CO2 injector and two water producers. For the reservoir, one oil producer (PRO1) and two injectors for water-alternating-gas (WAG) purposes (CO2_Oil and WAG_INJ) were used. For sequestration into the aquifer, a total of 32.787 million scf/D of CO2 was injected through CO2_AQ for 10 years. To balance the pressure and mitigate pressure buildup above the fracture gradient, water was produced through the two water producers. This water was reused for water injection into the reservoir. As part of the base case, the WAG process was designed with cycles of 8-month CO2 injection followed by 8-month water injection for a total of 10 years. The injection rates for both were 32.787 million scf/D and 11,000 STB/D, respectively.

Implementing reservoir characterization by undertaking seismic inversion on time-lapse surveys is very effective for observing the distribution and changes in the hydrocarbon reservoir. In mature oilfields, these changes are most likely influenced by the thermodynamic activities including the injection of fluid into the reservoir, which can change the volume, pressure, and composition of the geological formations. Fluid injection (in this case, water injection) into the reservoir is typically used as an oil and gas booster to increase production through EOR (Enhanced Oil Recovery). However, in light of CCUS (Carbon Capture Utilization and Storage) application, injecting CO2 can be considered as a new EOR strategy development, with the dual objectives of increasing oil and gas production as well as lowering carbon emissions at the same time. The 4-dimensional (4D) seismic data available over Widuri Field covers an area of 125 km2, with 884 inlines and 905 crosslines, acquired in 1991 and 2004 over the same area. The inversion algorithm is using seismic deconvolution to generate an acoustic impedance model before developing a geological reservoir model. Reservoir characterization was conducted in this study to obtain detailed information of the reservoir zones by determining the impact of water injection that replaces hydrocarbons. Intervals and areas with an abundance of water can be considered as potential CO2 sequestration in the future, as a part of the CCUS application. In conclusion, the findings of increasing impedance from inversion data from 1991 to 2004 can indicate the presence of existing porosity and permeability. This evidence could indicate reservoir capability as CO2 storage.

Against the global backdrop of carbon neutrality, technological revolution, and deep oil development strategies, the advancement of large-scale integrated technologies for CO₂ geological utilization and sequestration (CO₂-GUS) holds strategic significance for safeguarding national energy security and mitigating climate change. Currently, century-scale geological sequestration and utilization of CO₂ remain heavily reliant on simulation and predictive methodologies, underscoring an urgent need to advance collaborative innovation between molecular design strategies and engineering application technologies. This paper focuses on recent progress in this field, systematically reviewing the design strategies of CO₂-responsive gels, self-adaptive foams, nano-bubbles, and supercritical CO₂ thickeners, with particular emphasis on molecular design principles for CO₂ affinity and deep subsurface adaptability. It analyzes the temperature and salt tolerance of CO₂-responsive gels and thickeners, as well as CO₂ mobility control mechanisms, reveals the synergistic mechanism of energy release enhancement and enhanced oil recovery (EOR) via CO₂ nano-bubble bursting, and clarifies the colloidal interfacial behavior of CO₂ self-adaptive foams. Furthermore, this study outlines future directions for advanced atomic force microscopy (AFM) characterization techniques at the molecular and atomic scales in CO₂-GUS applications. It also evaluates the engineering performance of these systems in synergistic CO₂-EOR and sequestration technologies, as well as in integrated CO₂ fracturing-EOR-sequestration processes. Finally, a century-scale deployment framework for CO₂ self-adaptive functional materials in geological utilization and sequestration is proposed, thereby providing a theoretical basis and technical support for the long-term safe management of CO₂.

On a worldwide scale, Trinidad and Tobago (T&T) produces less than 1% of global greenhouse gas (GHG) emissions, with the largest emissions stemming from its power generation, transportation, and industrial sectors. The EOR 26 reservoir was modelled using the Computer Modelling Group (CMG) software. Comparing the original oil in place (OOIP) from the IMEX model (1.83 MMSTB) to the actual OOIP (1.87 MMSTB) gave only a 0.04 MMSTB difference, which was close enough to match the model, injection and production data. The CMOST program in CMG was used to identify the parameters that significantly affected the model (using the Sobol Analysis). Simulations were conducted for each scenario, and a comprehensive data analysis and economic evaluation were conducted. Scenario 4 was the most favourable since it runs for 69 years (as opposed to 100 years), sequesters the most volume of CO2 (85.6 MtCO2), produces the most oil volume (1.4 mmbbls) and gives a positive NCF for a range of oil price sensitivities. The NPV of this project at a 15% discount rate was calculated to be 0.23 MMUSD and the payback period was less than 2 years. The economic evaluations can be improved by aligning costs and revenue closer to the T&T framework.

Geological carbon sequestration requires injecting CO2 into the deep formation through wellbores with an injection rate as high as ~1 Mt/year. This process can lead to substantial temperature drops near the wellbore, potentially causing the cement debonding from the casing or formation, resulting in severe leakage. In this paper, we first analyzed the transient wellbore temperature and pressure profile across the well's depth using both an analytical model and one dynamic multiphase flow simulator, with cross validation. We then adapted these results for the subsequent well integrity analysis using a fully coupled thermoporoelastic model with transient solutions. Our analysis shows that the cooling effect depends on injection rate, surface CO2 temperature, and reservoir pressure. For a simulated Class VI well, a combination of high injection rate, low surface CO2 temperature, and depleted reservoir could result in the wellbore temperature that close to the bottom dropping by 60 ℃. Similar significant cooling scenarios have been observed at the Aquistore field located in Canada, the Alwyn field, and the Goldeneye field in the U.K. The maximum allowable cooling temperature for a typical cement formulation with 10 GPa elastic modulus, and 0.15 Poisson's ratio is 40 ℃. Therefore, this cooling effect could compromise wellbore integrity and cause well leakage through cement-casing debonding. Multiple practical strategies have been found to enhance cement integrity during CO2 injection, including modifying cement formulation to be more ductile and resilient, enhancing the initial state of stress in the cement using a pre-stressing method or expansive additive, and adding an insulated coating layer to the tubing. Pre-heating CO2 at the surface is effective but can be expensive and impractical. Using a protective annulus fluid with a lower thermal conductivity and a new tubing material with low thermal conductivity have been found to be ineffective. Overall, our comprehensive analysis enables us to assess the long-term impacts of CO2 injection on well integrity and promote sustainable and effective geological carbon sequestrations with proper environmental protection protocols.

During the Development Phase of the U.S. Southwest Regional Partnership on Carbon Sequestration, supercritical CO2 was continuously injected into the deep oil-bearing Morrow B formation of the Farnsworth Unit in Texas for Enhanced Oil Recovery (EOR). The project injected approximately 94 kilotons of CO2 to study geologic carbon storage during CO2-EOR. A three-dimensional (3D) surface seismic dataset was acquired in 2013 to characterize the subsurface structures of the Farnsworth site. Following this data acquisition, the baseline and three time-lapse three-dimensional three-component (3D-3C) vertical seismic profiling (VSP) data were acquired at a narrower surface area surrounding the CO2 injection and oil/gas production wells between 2014 and 2017 for monitoring CO2 injection and migration. With these VSP datasets, we inverted for subsurface velocity models to quantitatively monitor the CO2 plume within the Morrow B formation. We first built 1D initial P-wave (Vp) and S-wave (Vs) velocity models by upscaling the sonic logs. We improved the deep region of the Vp and Vs models by incorporating the deep part of a migration velocity model derived from the 3D surface seismic data. We improved the shallow region of 3D Vp and Vs models using 3D traveltime tomography of first arrivals of VSP downgoing waves. We further improved the 3D baseline velocity models using elastic-waveform inversion (EWI) of the 3D baseline VSP upgoing data. Our advanced EWI method employs alternative tomographic and conventional gradients and total-variation-based regularization to ensure the high-fidelity updates of the 3D baseline Vp and Vs models. We then sequentially applied our 3D EWI method to the three time-lapse datasets to invert for spatiotemporal changes of Vp and Vs in the reservoir. Our inversion results reveal the volumetric changes of the time-lapse Vp and Vs models and show the evolution of the CO2 plume from the CO2 injection well to the oil/gas production wells.

We study in detail the pressure stabilizing effects of the non-iterated fixed-stress splitting in poromechanical problems which are nearly undrained and incompressible. When applied in conjunction with a spatial discretization which does not satisfy the discrete inf-sup condition, namely a mixed piecewise linear - piecewise constant spatial discretization, the explicit fixed-stress scheme can have a pressure stabilizing effect in transient problems. This effect disappears, however, upon time step refinement or the attainment of steady state. The interpretation of the scheme as an Augmented Lagrangian method similar to Uzawa iteration for incompressible flow helps explain these results. Moreover, due to the slowly evolving solution within undrained seal regions, we show that the explicit fixed-stress scheme requires very large time steps to reveal its pressure stabilizing effect in examples of geologic CO$_2$ sequestration. We note that large time steps can result in large errors in drained regions, such as the aquifer or reservoir regions of these examples, and can prevent convergence of nonlinear solvers in the case of multiphase flows, which can make the explicit scheme an unreliable source of pressure stabilization. We conclude by demonstrating that pressure jump stabilization is as effective in the explicit fixed-stress setting as in the fully implicit setting for undrained problems, while maintaining the stability and convergence of the fixed-stress split for drained problems.

The development and monetization of gas fields with high CO2 content is a key strategy for PETRONAS to support sustainability goals and meet gas demand. However, a major challenge in this type of development is the significant CO2 emissions exceeding targeted limits for greenhouse gases and CO2 reduction towards achieving net zero emissions by 2050. Therefore, decarbonization becomes essential for sustainable development, leading to the consideration of sequestering produced CO2 as a practical solution. This paper examines the feasibility of recycling produced CO2 for sequestration purposes in a Malaysian gas field containing approximately 60% CO2 content, aiming to explore simultaneous gas production and injection of CO2 into the same geological formation during field development. High-level integrated containment analysis was conducted to verify containment for the shortlisted potential targets in Z field through typical geology process which mostly related to reservoir characterization, reservoir correlation, sedimentology, and structural configuration. The integrated containment analysis results were identified 14 non-associated gas (NAG) potential targets, 11 normal-pressure zones and 3 over-pressure zones with different level of risks. A field cross-section scenario map was established by considering three different possible cases and three different risk levels from integrated containment analysis to address complexity field geological structure and the plan for subsurface development. The injection and development scenarios were included two options, in-situ CO2 sequestration scenario through simultaneous injection & production plan for gas zones and CO2 injection in pure saline aquifers. The capacity estimation results for Z field shows there is an approximately 3 TSCF potential theoretical storage capacity. Also, the capacity estimation results using analogue analyses shows there is an approximately 754 BSCF potential effective storage capacity. However, it is decided to exclude saline aquifer option during development with only 3% contribution to effective storage volume and it is due to higher uncertainties, less well penetration/data availability, and need for considering water producer and making artificial depletion to make desire injection as per plan. CCUS-EOR can be an option for oil rim development with ~ CR=7.6 MMstb, potential oil recovery of ~3.8 MMstb, RF=50%. It requires to produce all gas/oil together and plan for proper re-recycling the injected CO2 to maximize the oil gain from CCUS. The study's overall conclusion validates the feasibility of recycling produced CO2 as a cost-effective option for developing high CO2 gas fields. This paper introduces groundbreaking approach to demonstrate the potential development of high CO2 gas fields with sequestration, aiming to achieve a net-zero carbon emission target and eliminate the need for transporting CO2 into flaring streams. Additionally, it proposes an integrated field and storage development plan that maximizes asset value by unlocking additional gas reserves and implementing appropriate CO2 management arrangements.

Data-driven and non-intrusive DMDc and DMDspc models successfully expedite the reconstruction and forecasting of CO2 fluid flow with acceptable accuracy margins, aiding in the rapid optimization of geological CO2 storage forecast and optimization. DMDc and DMDspc models were trained with weekly, monthly, and yearly simulation pressure and CO2 saturation fields using a commercial simulator. The domain of interest is a large-scale, offshore, highly heterogeneous reservoir model with over 100,000 cells. DMD snapshot reconstruction significantly reduced simulation times from several hours to mere minutes. DMDspc reduced the number of DMD modes for pressure without losing accuracy while sometimes even improving accuracy. Two operation cases were considered: 1. CO2 injection, 2. CO2 injection and water production for pressure maintenance. For pressure, DMDspc achieved a slightly higher than DMDc average error by removing several modes. On the other hand, DMDspc showed limited success in reducing modes for CO2 saturation. The forecast performance of DMD models was evaluated using percent change error, mean absolute error and Pearsons R correlation coefficient metrics. Almost all DMD pressure models managed to successfully forecast pressure fields, while a smaller number of DMD models managed to forecast CO2 saturation. While forecast errors have a considerable range, only DMD models with errors below 5% PCE for pressure or 0.01 MAE for saturation were considered acceptable for geological CO2 storage optimization. Optimized CO2 injection and water production amounts were consistent across selected DMD models and all time scales. The DMDspc-monitored cells approach, which only reconstructs the monitored-during-optimization cells, reduced even further optimization time while providing consistent results with the optimization that used full snapshot reconstruction.

CO2 storage in geological formations, particularly deep saline aquifers, is a critical component of carbon capture and storage technology, offering significant potential for mitigating greenhouse gas emissions. However, high salinity of these aquifers poses the risk of salt precipitation, leading to pressurization and injectivity reduction. Developing a method to prevent salt precipitation remains a challenge, and this is an area that this study is focused on. Dissolved-water CO2 injection (dwCO2 injection) is proposed here as a novel method to prevent salt precipitation where water is dissolved in CO2 before injection into an aquifer. Presence of water in the CO2 stream prevents more dissolution of water into CO2 (evaporation) and, hence, prevents salt precipitation. Before presenting this method and in order to provide a good mechanistic understanding of the interactions involved in a CO2 storage process, six different scenarios are examined using the CMG-GEM simulator within a carbonate aquifer. The results showed that saturating CO2 with water reduced the precipitation nearly to zero, and dissolving 2000 ppmv water decreased the salt precipitation to one-third. It should be noted that injection of humid CO2 requires special methods to tackle the potential challenges, including corrosion and hydrate formation risks, and the paper also discusses them.

No abstract available

This paper aims to understand the interplay between injection rate, water vaporization, and capillary backflow on halite precipitation when injecting dry CO2 into a saline aquifer, and the potential injectivity impairment. Key processes affecting salt precipitation include two-phase displacement of brine, dry-out and capillary-driven backflow. In this work, we developed 1D and 2D thermal-compositional radial models with fine gridding around the wellbore and strongly controlled timesteps to study the effects of CO2 injection at different rates using a commercial reservoir simulator (GEM). The initial reservoir conditions were 300 bars, 109 °C, and salinity of 49 g/L. We applied a porosity-permeability relationship from the Verma and Muller (1988) model, which implies complete permeability reduction when porosity decreases by 9%. Simulations were performed with and without capillary pressure effects. After performing some sensitivities to the grid-block size, a fine grid resolution (0.1-0.2 m) near the well is needed at relative low CO2 injection rates due to capillary effects. While less critical at high injection rates, grid refinement still influences precipitation onset at higher rates. We found that a 0.2 m near-well grid size offers a practical balance between accuracy and computational efficiency when simulating salt precipitation during the CO2 injection in saline aquifer. The 1D results show that at zero capillary pressure, impairment is independent of the injection rate, with only 1% of pore volume occupied by salt precipitation, corresponding to the salt mass contained in the immobile brine. However, with non-zero capillary pressure, capillarity can cause significant backflow, bringing additional brine to the near-wellbore area, resulting in higher amounts of precipitated salt. High injection rates shorten the exposure time to capillary backflow with rapid water vaporization and less salt precipitation in the wellbore. Conversely, at low injection rates, brine backflow effectively compensates water vaporization, bringing more brine from the reservoir to the well. This increases solid salt accumulation around the wellbore and reduces permeability. An injection rate as low as 0.1 MTPA may block well injectivity due to high solid saturation, whereas an injection rate of 1 MTPA may partially impair injectivity with only 2% solid saturation around the well. Gravity effects on solid precipitation were analysed by modeling CO2 injection in a 2D radial model. More optimistic results were obtained compared to the 1D model, indicating that some level of impairment can be expected in the well section with low injection flow rates. However, other sections can continue injection with weak permeability reduction even when injecting CO2 at 0.1 MTPA. In general, injectivity is partially impaired, but CO2 injection may proceed with some loss of injectivity and higher bottom-hole pressure. A capillary number defined as the ratio of viscous to capillary forces seems effectively to characterize the dominant forces influencing halite precipitation during the dryout period. High capillary numbers (high injection rates) result in minimal impairment, while intermediate values show a balance leading to moderate damage. Low capillary numbers (low injection rates) are associated with strong capillary backflow and severe permeability reduction. The dry-out time is significantly extended at low injection rates due to capillary backflow. The dimensionless capillary number can be used to predict formation damage and injectivity changes for similar reservoir conditions. However, further work is needed to generalize these findings across a wider range of parameters. This study offers valuable insights into halite precipitation mechanisms during CO2 injection in saline aquifers, important for optimizing injection strategies and mitigating well impairment. By understanding the interplay between injection rate, water transport by CO2, and capillary forces, we can better predict and manage salt precipitation risks.

Carbon dioxide (CO2) flooding is one of the most important and most used enhanced oil recovery (EOR) method because it does not only increase oil recovery efficiency but also is used as an underground CO2 storage. It is considered a very complex method as it involves knowing the fluid phase behavior with different CO2 concentrations. It should be noted that oil swelling (volume increase) with the dissolution of carbon dioxide has a significant effect on increase of oil recovery. When this occurs, a significant decrease in the viscosity of the oil is observed. In this study, a reservoir 3D simulation modeling approach was applied to evaluate immiscible and miscible CO2 flooding in a high WC reservoir. To reduce simulation time, the PVT composition was grouped into 5 fluid components. The 3-parameter, Peng-Robinson Equation of State (EOS) was used to match PVT experimental data by using the Schlumberger's ECLIPSE PVTi software. One-dimensional slim-tube model was defined using ECLIPSE 300 software to determine the minimum miscibility pressure (MMP) for injection of CO2. Beside this approach, an analytical MMP estimation was carried out using several correlations. Schlumberger Petrel software was used to set up a 3D simulation model of a static and dynamic model. Various scenarios of immiscible and CO2 injection have been simulated using ECLIPSE 300 software and these results have been compared.

The geological storage of CO2 in saline aquifers is a crucial method for achieving large-scale carbon storage in the future. The saline aquifers with low porosity and permeability in the Ordos Basin exhibit high irreducible water saturation and restricted fluid mobility, necessitating further investigation of their injectivity and storage safety. The fifth member of the Shiqianfeng Formation (P3sh5) in the Ordos Basin serves as a key layer for geological CO2 storage (GCS). The numerical simulation of CO2 injection in this reservoir is an indispensable process for characterizing the migration and storage of CO2. Injection pressure and well type (vertical well or horizontal well) are critical factors affecting GCS. The results of the numerical simulation are important preliminary preparations for promoting the GCS in the saline aquifer of the Shiqianfeng Formation in the future. This paper focuses on P3sh5 in the Yulin area as a case study. It investigates the injectivity and CO2 migration characteristics of these low porosity and low permeability saline aquifers in the Ordos Basin. Relatively high-quality distributary channel sandstone bodies in integrally low porosity and permeability strata were identified for injection. As CO2 is injected, the formation pressure gradually increases. It is essential to maintain it below the fracture pressure during CO2 injection to ensure safety. High-pressure (8 MPa) injection could achieve volumes 2.9 times greater than those in the low-pressure scenario (4 MPa) of 2 km horizontal branch well. Under the three injection well types, the injection rate of vertical wells is the lowest. Employing a “horizontal branch well injection” strategy could potentially amplify the injection volume by 2.87 times. CO2 predominantly migrates vertically near the horizontal interval of interest, while horizontally, the area near the interval of interest experiences a higher CO2 saturation, with the maximum saturation reaching about 50%. Overall, CO2 is migrated in the distributary channel sandstone bodies, indicating a higher storage safety and lower leakage risk. It is recommended that the number of drilling wells be increased and multiple horizontal branch wells implemented to enhance the injection efficiency. Overall, this study provides a geological foundation for the previous design and construction of the GCS project in the Ordos Basin’s saline aquifer. It also provides a reference for GCS in low permeability saline layers in similar regions worldwide.

To obtain the maximum field oil recovery (FOR) and CO2 sequestration ratio (CSR), it is imperative to optimize the CO2 injection and liquid production rate. However, previous studies ignore the geomechanical risks indeed. Therefore, a hybrid optimization framework was designed that combines artificial intelligence methods (Support Vector Regression with the Gaussian kernel, Gaussian-SVR or Long Short-Term Memory, LSTM) and multi-objective optimization algorithms (multiple objective particle swarm optimization, MOPSO or Non-dominated Sorting Genetic Algorithm II, NSGA-II) to find the optimal CO2 injection and production strategies under different water cut. With this framework, the largest oil recovery and CO2 storage under the lowest fault slip displacement (FSD) can be obtained simultaneously. In this framework, Latin hypercube sampling (LHS) is used to produce the samples for training and testing for cases with water cut 0.7, 0.8, 0.9 and 0.95, and the corresponding results are obtained from numerical simulations. Thus, Gaussian-SVR and LSTM are trained as the proxy model to substitute the numerical simulator. Thus, the MOPSO and NSGA-II are utilized to determine the Pareto Front of the optimum result and work schedules. A synthetic case reservoir model with high-water cut and one fault is employed to test the robustness of this framework. The results show that compared with FOR and CSR, due to the serious nonlinearity, the training and prediction of FSD with the proxy model are not very good. The prediction errors increase with the water cut, and when the field water cut is larger than 0.9, the practical requirements (± 20% errors) are not yet met. In general, the performance of proxy model with LSTM is superior to the Gaussian-SVR. The solutions obtained from the Pareto optimal set for the NSGA-II algorithm exhibit faster convergence, better superiority and reliability than MOPSO. As the rise of water cut, the optimal average field gas injection rate (FGIR) decreases, while the average field liquid production rate (FLPR) increases. The novelty of this work mainly lies in the consideration of fault slip during CO2 injection for multi-objective optimization in high-water cut oil reservoirs, which can provide some guidance for the design of schemes.

Salt precipitation, induced by the dry-out effect in the CO2 injection process, reduces the reservoir porosity and impairs the permeability in the vicinity of the wellbore, further impacting the CO2 injectivity. Accurately predicting and understanding the distribution and growth of salt precipitation in porous media near the wellbore is essential for optimizing CO2 injectivity in saline aquifers. In this work, a comprehensive model is established to simulate the dynamics of salt precipitation, incorporating the coupled effects of fluid flow, salt transport, and evaporation-induced salt concentration changes. The impacts of local heterogeneity and surface wettability on salt distribution are explored within various porous media. In addition, the effects of capillary-driven backflow are considered, which have the potential to alter salt transport and accumulation. By simulating these interactions under varying reservoir conditions, the model accurately captures the spatial and temporal dynamics of salt precipitation, enabling an in-depth understanding of the factors that contribute to injectivity impairment. The simulation results show that altering the direction of CO2 injection has minimal influence on salt distribution within homogeneous porous media. However, localized decreases in porosity and permeability arise from the nucleation and aggregation of salt, altering capillary forces and instigating the movement of water from regions of higher to lower water saturation. This heterogeneity leads to uneven salt deposition, with more pronounced salt accumulation in regions where lower permeability zones impede fluid movement, further exacerbating the local changes in porosity and permeability. Strongly water-wet porous media exhibits a higher rate of salt precipitation compared to the intermediate-wet conditions due to a faster rate of water evaporation, resulting in more substantial permeability reductions. Capillary-driven backflow enhances the migration of saline fluids into less saturated zones, causing non-uniform salt accumulation and localized permeability declines. This work predicts variations in salt distribution under different conditions. The consideration of localized fluid dynamics offers significant advancements in understanding and managing the impact of salt precipitation on reservoir permeability and injectivity, addressing one of critical challenges in CO2 sequestration.

Injecting CO2 into deep saline aquifers is a prominent strategy for carbon capture and storage (CCS) to mitigate greenhouse gas emissions. However, ensuring the long-term integrity of CO2 storage is crucial to prevent leakage and potential environmental hazards. This paper investigates the impact of fracture permeability on CO2 leakage volumes in the context of CO2 injection into Syderiai deep saline aquifer for carbon capture and storage (CCS) applications. It explores the relationship between fracture permeability and the potential for CO2 leakage, as well as the volume of CO2 dissolved in water above and below the cap rock. Furthermore, the study examines how the leakage volume may evolve over time in Syderiai deep saline aquifer. A mechanistic model of Syderiai deep saline aquifer, of Lithuanian basin, was developed based on average permeability, porosity, NTG and thickness (Fig. 1) and is used in this analysis.

In the development of edgewater-type carbonate gas reservoirs, the challenge posed by water flooding in production wells is a significant concern. This study investigates the potential of CO2 injection as a solution for water control. Experiments were conducted to understand the gas–water flow dynamics during CO2-controlled water injection in a series-connected core. Emphasis was placed on the effects of varying the CO2 injection pressure on water flow and gas cumulative production rate. The mechanisms influencing water control and production efficiency across different injection pressures in multiwell production were elucidated. The results showed that the gas production rate of the core increased by 27.2% over the depletion production rate after the CO2 injection pressure was increased from 8 to 13 MPa. The gas production rate increases during the second development cycle from 20% to 55% after switching to CO2 injection, which pushes the edge water further back, slowing down side water flow in the core in the form of segmental plugs, and prolonging the time before water breakthrough. The production time and water breakthrough time for the second development cycle increased with increasing CO2 injection, while the degree of water flow on the core side decreased. These insights are crucial for optimizing the recovery efficiency of edgewater-type gas reservoirs and provide guidance on the application of CO2 injection for water control and CO2 sequestration in carbonate gas reservoirs.

This study explores the numerical modeling of CO2 injection in water within a lab-scale domain, where the dimensions are in the order of centimeters, highlighting its diverse applications and significant environmental and economic benefits. The investigation focuses on the impacts of heterogeneity, capillary pressure, and CO2 viscosification on water production. Findings reveal that increasing CO2 viscosity by a factor of 5 drastically influences water production, while further increasing it to a factor of 10 yields minimal additional effect. Capillary pressure notably delays breakthrough and reduces sweeping efficiency (effectiveness of the injected CO2 in displacing water), with a more pronounced impact in slim cores (1 cm) compared to thick cores (3.8 cm). The numerical modeling of CO2 injection in water within a lab-scale domain provides valuable insights into enhanced oil recovery (EOR) techniques. These optimized strategies can improve the efficiency and effectiveness of CO2-EOR, leading to increased oil and gas recovery from reservoirs.

: CO 2 injection has been deemed a promising method for CH 4 production from gas hydrate-bearing sediments for its potential in stabilizing the host sediments and balancing carbon emission. However, the process is yet to be fully understood, as it involves interactions of multi-physical and chemical processes including the generation of water-immiscible CH 4 − CO 2 fluid mixtures, the evolution of chemical reaction kinetics for both CH 4 and CO 2 hydrates, heat emission and absorption during hydrate formation and dissociation, and stress redistribution caused by spatially evolving responses of CH 4 − CO 2 hydrate-bearing sediments. This paper develops a coupled thermo-hydro-chemo-mechanical formulation that captures the complexity of these processes and applies it to investigate the behavior of CH 4 hydrate-bearing sediments subjected to CO 2 injection. The capabilities of this coupled formulation are validated through numerical simulations of laboratory experiments of CO 2 injection into CH 4 hydrate-bearing soil. Moreover, the application of this formulation in a field-scale scenario reveals insights into the efficiencies of CH 4 production and CO 2 storage and the geomechanical implications. Notably, the study finds that compared to the depressurization-only method, the combined hot CO 2 injection and depressurization method could increase CH 4 production by approximately 400%. In addition, this method could sequester about 70% of injected CO 2 into solid hydrates, while exhibiting smaller maximum slope of differential displacement. These outcomes highlight the viability and benefits of CH 4 hydrate production through CO 2 injection, increasing the prospects of this approach.

Enhancing oil recovery in reservoirs with light oil and high gas content relies on optimizing the miscible water alternating gas (WAG) injection profile. However, this can be costly and time-consuming due to computationally demanding compositional simulation models and numerous other well control variables. This study introduces WAGeq, a novel approach that expedites the convergence of the optimization algorithm for miscible water alternating gas (WAG) injection in carbonate reservoirs. The WAGeq leverages production data to create flexible solutions that maximize the net present value (NPV) of the field, while providing practical implementation of individual WAG profiles for each injector. The WAGeq utilizes an injection priority index to rank the wells and determine which should inject water or gas at each time interval. The index is built using a parametric equation that considers factors such as producer and injector relationship, water cut (WCUT), gas–oil ratio (GOR), and wells cumulative gas production, to induce desirable effects on production and WAG profile. To evaluate WAGeq’s effectiveness, two other approaches were compared: a benchmark solution named WAGbm, in which the injected fluid is optimized for each well over time, and a traditional baseline strategy with fixed 6-month WAG cycles. The procedures were applied to a synthetic simulation case (SEC1_2022) with characteristics of a Brazilian pre-salt carbonate field with karstic formations and high CO2 content. The WAGeq outperformed the baseline procedure, improving the NPV by 6.7% or 511 USD million. Moreover, WAGeq required fewer simulations (less than 350) than WAGbm (up to 2000), while delivering a slightly higher NPV. The terms of the equation were also found to be essential for producing a WAG profile with regular patterns on each injector, resulting in a more practical solution. In conclusion, WAGeq significantly reduces computational requirements while creating consistent patterns across injectors, which are crucial factors to consider when planning a practical WAG strategy.

No abstract available

Injecting captured CO2 into geological formations is a cornerstone of climate change mitigation, but ensuring the long-term integrity of Carbon Capture and Storage (CCS) wells presents unique material challenges. Standard oil and gas material selection guidelines[1] offer a starting point, yet they often fall short in addressing the specific threats posed by dense-phase CO2 streams containing corrosive impurities. Corrosion fundamentally requires water; while the water content of the injected CO2 can be controlled at the surface, the uncontrollable flowback of saline formation water during inevitable shut-in periods poses a significant threat, directly wetting critical components like tubing and liners. This paper chronicles the journey undertaken to select appropriate tubing materials facing this complex challenge, compounded by corrosive H2S, impacts of transient oxygen (O2) ingress and potential low temperatures arising from Joule-Thomson effects or operational upsets. The presence of even ppm levels of O2 can drastically alter corrosion mechanisms, while low temperatures demand proven material toughness, especially when coupled with corrosive formation brine. Faced with a lack of standardized limits for these combined conditions, a rigorous qualification testing program became paramount. This study details the systematic approach taken, starting with identifying candidate Corrosion Resistant Alloys (CRAs) – S13Cr, 17Cr, and S25Cr – balancing cost and perceived performance. A comprehensive test matrix was designed to simulate normal operating (base-case) and design (worst-case) scenarios (up to 50 ppm H2S, 10 ppm O2, 135 degC, 12800 ppm Cl- from formation water, pH ~3), including dedicated evaluations for Sulphide Stress Cracking (SSC), Stress Corrosion Cracking (SCC), general/localized corrosion, and galvanic compatibility. The phased testing sequence, including crucial assessments of O2‘s impact and confirmed the robustness of 17Cr, especially when galvanic risks were mitigated by simulating realistic area ratios and copper plating. This investigation provides a practical roadmap for qualifying materials in complex CCS environments, highlighting the potential of 17Cr as a cost-effective and technically sound solution, contingent upon the successful implementation of galvanic corrosion mitigation strategies.

Carbon dioxide (CO2) injection in unconventional gas-bearing shale reservoirs is a promising method for enhancing methane recovery efficiency and mitigating greenhouse gas emissions. The majority of methane is adsorbed within the micropores and nanopores (≤50 nm) of shale, which possess extensive surface areas and abundant adsorption sites for the sequestration system. To comprehensively discover the underlying mechanism of enhanced gas recovery (EGR) through CO2 injection, molecular dynamics (MD) provides a promising way for establishing the shale models to address the multiphase, multicomponent fluid flow behaviors in shale nanopores. This study proposes an innovative method for building a more practical shale matrix model that approaches natural underground environments. The grand canonical Monte Carlo (GCMC) method elucidates gas adsorption and sequestration processes in shale gas reservoirs under various subsurface conditions. The findings reveal that previously overlooked pore slits have a significant impact on both gas adsorption and recovery efficiency. Based on the simulation comparisons of absolute and excess uptakes inside the kerogen matrix and the shale slits, it demonstrates that nanopores within the kerogen matrix dominate the gas adsorption while slits dominate the gas storage. Regarding multiphase, multicomponent fluid flow in shale nanopores, moisture negatively influences gas adsorption and carbon storage while promoting methane recovery efficiency by CO2 injection. Additionally, saline solution and ethane further impede gas adsorption while facilitating displacement. Overall, this work elucidates the substantial effect of CO2 injection on fluid transport in shale formations and advances the comprehensive understanding of microscopic gas flow and recovery mechanisms with atomic precision for low-carbon energy development.

Carbon capture and storage (CCS) has been recognized as a pivotal technology for mitigating climate change by reducing CO2 emissions. Storing CO2 in deep saline aquifers requires preserving the water-wet nature of the formation throughout the storage period, which is crucial for maintaining rock integrity and storage efficiency. However, the wettability of formations can change upon exposure to supercritical CO2 (scCO2), potentially compromising storage efficiency. Despite extensive studies on various factors influencing wettability alteration, a significant research gap remains in understanding the effects of different CO2 injection strategies on wettability in deep saline formations (DSFs). This study addresses this gap by investigating how three distinct CO2 injection strategies—continuous scCO2 injection (CCI), water alternating with scCO2 injection (WAG), and simultaneous water and scCO2 injection (SAI)—affect the wettability of gray Berea sandstone and Indiana limestone, both selected for their homogeneous properties relevant to CCS. Using a standardized sessile drop contact angle method before and after CO2 injection, along with core flooding to model the injection process at an injection pressure of 1500 psi and temperature of 100 °F with a confining pressure of 2500 psi, the results indicate a shift in wettability towards more CO2-wet conditions for both rock types under all strategies with changes in CA of 61.6–83.4° and 77.6–87.9° and 81.5–124.2° and 94.6–128.0° for sandstone and limestone, respectively. However, the degree of change varies depending on the injection strategy: sandstone exhibits a pronounced response to the CCI strategy, with up to a 77% increase in contact angle (CA), particularly after extended exposure. At the same time, WAG shows the least change, suggesting that water introduction slows surface modification. For limestone, the changes in CA ranged from 9% to 49% across strategies, with WAG and SAI being more effective in altering its wettability. This study underscores the importance of selecting suitable CO2 injection strategies based on rock type and wettability characteristics to maximize carbon storage efficiency. The findings offer valuable insights into the complex interactions of fluid–rock systems and a guide for enhancing the design and implementation of CCS technologies in various geological settings.

This study evaluates the feasibility of CO2 Water-Alternating-Gas (WAG) injection for enhanced oil recovery (EOR) in a highly heterogeneous reservoir using cost-effective and efficient tools. The Rule of Thumb method was initially used to screen the reservoir, confirming its suitability for CO2-WAG injection. A fluid model was constructed by comparing several component lumping methods, selecting the approach with the least deviation from experimental data to ensure accuracy. The minimum miscibility pressure (MMP), a critical parameter for CO2-EOR, was estimated using three methodologies: 1D simulation based on the slim tube test, semi-empirical analytical correlations, and fluid modeling. These techniques provided complementary insights into the reservoir’s miscibility conditions. The CO2 Prophet software version 1 was employed to history-match production data and evaluate different development strategies. The Kinder Morgan CO2 Scoping Model was used to perform production forecasting and assess the economic viability of implementing CO2-WAG. Quantitative comparisons showed that the CO2 Prophet version 1 model revealed minimal deviations from the history match results: oil production estimates differed by only 3.5%, and water production estimates differed by −4.11%. Cumulative oil recovery was projected to reach approximately 20.26 MMSTB over a 25-year production period. The results indicate that CO2-WAG injection could enhance oil recovery significantly compared to water flooding while maintaining economic feasibility. This study demonstrates the practical integration of analytical tools and inexpensive models to evaluate and optimize CO2-EOR strategies in complex reservoirs. The findings provide a systematic workflow for deploying CO2-WAG in heterogeneous reservoirs, balancing technical and economic considerations.

In the future, there will be competition among natural gas, CO2, and hydrogen for suitable geological storage sites. Therefore, it is crucial to evaluate all of the potential storage options. One promising option is the utilization of fractured carbonate rocks, which offer significant opportunities for gas sequestration in depleted reservoirs and saline aquifers. The objective of this study is to assess the feasibility of using carbonate matrix rocks in saline aquifers for carbon capture and storage (CCS) projects. Although carbonate reservoirs are currently not ranked highly for carbon storage due to the risk of CO2 leakage, their matrix rock with reactive minerals like calcite and dolomite, along with the possibility of natural fractures, presents an interesting opportunity. This research proposes a reassessment of the role of fractures, which are typically viewed as a risk factor, within a novel and integrated context. It combines geochemical modeling with numerical models that incorporate two distinct density levels of natural fractures. The interactions between the carbonate matrix, the formation brine, and the injected CO2 can lead to water vaporization and the deposition of evaporite minerals, known as the halite scale, within the porous medium. These minerals can be transported within highly conductive fractures that possess a permeability 100 times greater than the matrix. The study findings indicate that the fractures become filled, creating a natural seal that prevents CO2 leakage through what was previously considered a potential pathway in both models and different initial pH values. Furthermore, the results demonstrate the formation of secondary minerals through the reaction of CO2 and its aqueous counterparts with rock matrix minerals. These minerals, including Dawsonite, are then deposited within fracture apertures, compensating for the dissolution of calcite from the matrix and reducing the risk of enhanced fracture conductivity during CCS operations. The deposition of halite scales in initially acidic-brine saturated aquifers and/or Dawsonite scales in initially alkaline-brine saturated aquifers serves to partially counterbalance the permeability enhancement resulting from calcite dissolution. This phenomenon makes carbonate rocks a more secure option and highlights their potential suitability for CCS projects. The existence of these scales acts as a protective barrier, reducing the risk of increased permeability and enhancing the integrity of the storage reservoir.

Optimizing oil recovery from mature reservoirs remains a key challenge in the petroleum industry. This study evaluates the efficiency of CO2-WAG injection compared to continuous CO2 and water flooding using a sector model of the X Oil Field. A compositional reservoir simulator was employed to analyze oil recovery under water-wet and mixed-wet conditions, incorporating three-phase relative permeability and wettability effects. The results show that continuous CO2 flooding yields the highest oil recovery, with water-wet systems outperforming mixed-wet reservoirs. CO2-WAG injection provides a balanced approach, enhancing recovery while enabling CO2 sequestration, but remains less effective than continuous CO2 flooding. Water flooding, though the least efficient in terms of oil recovery, demonstrates long-term production stability. The gas–oil ratio (GOR) is notably higher in CO2-WAG, indicating gas breakthrough challenges. These findings emphasize the significant role of wettability in enhanced oil recovery (EOR) and suggest that continuous CO2 flooding is the most effective technique for maximizing production in heterogeneous reservoirs. This study contributes valuable insights for optimizing injection strategies, improving hydrocarbon recovery, and supporting sustainable reservoir management.

One of the Enhanced Oil Recovery (EOR) strategies in the petroleum industry is CO2 injection using the huff and puff method. The method is performed on one well that acts as an injection and a production well. The method works by injecting a certain volume of carbon dioxide (CO2) gas into the reservoir and then closing the well for a period of time. This injection cycle can take place over several cycles. Production can be carried out after one or more cycles according to the design. In this study, CO2 injection optimization with the huff and puff method is carried out with reservoir simulation (GEM-CMG) by taking data from one of the oil and gas wells in Indonesia, with carbonate rock characteristics that are water wet. The simulation work steps include inputting data (fluid, rock properties, and production), initialization, history matching, and CO2 injection optimization with the huff and puff method. The optimization scenarios include optimization of injection pressure and number of cycles. The injection pressure scenario uses a range of 500 - 3000 psi, based on the simulation results obtained that the injection pressure of 500 psi produces the highest recovery factor (RF) of 22.2%. Then, the cyclic scenario was carried out at the optimum injection pressure (500 psi) with the number of cycles 2 - 6 cycles. From the simulation results, it is found that the number of cycles for this carbonate reservoir condition does not have a significant effect, as evidenced by the RF values ranging from 22.1 - 22.3%.

Fast-objective function estimators (FOFE) are often used to speed up reservoir management. This work presents a FOFE constructed with the parametric Dynamic Mode Decomposition (DMDp) method for a carbonate reservoir with WAG-CO2 injection. The FOFE results are then compared to simulation results to analyze the FOFE's efficiency. We present an example of how changes in the production strategy can affect reservoir behavior. The FOFE utilizes snapshots of gas and water saturation of numerical simulation runs with different sizes of WAG-CO2 cycles to predict the snapshots and fluid rates of a production strategy with a desired WAG-CO2 cycle size. The FOFE utilizes the DMDp method to calculate the saturation snapshots and material balance equations to calculate oil, water, and gas rates. Unlike the standard where snapshots are stacked up for multiple parameters, leading to increased computational costs, here we perform interpolation directly on the reduced Koopman operator. This leads to enhanced performance as the time eigenvalues are no longer shared between all parameters. The case study is the public access benchmark UNΊSFM-ΓV-2022, a carbonate reservoir model with characteristics of the Brazilian pre-salt. This model represents a developed reservoir with a WAG-CO2 recovery method for a compositional simulator with historical data. For this work, the FOFE utilizes snapshots of two reservoir simulations, one with a WAG-CO2 cycle size of 6 months and the other with 18 months, to predict the states of a production strategy with 12 months of WAG-CO2 cycle. The FOFE results of gas, oil, and water are compared to a simulation result with the same production strategy. The comparisons for fluid dynamics are shown for reservoir conditions, and their curves with relative differences are provided. The FOFE can predict the states of a different field scenario, dispensing the necessity of extra numerical simulation runs. This result is promising for production optimization problems which require a significant amount of simulation runs to incorporate the many reservoir uncertainties, as it is observed in highly heterogeneous carbonate reservoirs. The innovation of this work is the utilization of the DMDp in a highly heterogeneous reservoir with three-phase flow and WAG-CO2 injection utilizing commercial software. This FOFE can be utilized to reduce the time and computational effort necessary for the decision-making process involving the control variable of WAG-CO2 cycle size.

CO2 injection is a promising solution for reducing atmospheric CO2 concentrations while enhancing subsurface storage capacity and production. This study investigates the phenomena that occur in carbonate reservoirs during CO2 injection. Specifically, we examined the effects of injecting CO2-saturated water on carbonate reservoir properties from Indonesia. Laboratory core flooding experiments were conducted to observe and analyse the chemical and physical processes induced by CO2 injection. The results can be used to design future CO2 injection scenarios and improve reservoir modelling. Experimental measurements revealed that CO2 and H2O react chemically with CaCO3, and the resulting reactions may reduce rock permeability due to CaCO3 precipitation or fine particle migration that clogs pore throats in carbonate reservoirs.

The Upper Urho Formation in the Mahu A well area features water - sensitive tight conglomerate reservoirs, mainly in P3w22, with 0.1 mD average permeability and strong water sensitivity. Early anti - swelling measures and horizontal well plus volume fracturing technology increased initial production, but couldn’t curb the steep production drop. To tackle these issues, a 280m five - spot vertical well pattern was adopted in the test area for a CO2 pre - injection pilot test. Based on logging interpretation of 18 completed wells, a detailed geological model was built. Numerical simulation optimized CO2 pre - injection perforation and injection parameters to guide the test plan. Simulation suggests little advantage in zonal gas injection, so it’s recommended to only perforate the middle and lower reservoirs of production wells. By October 2024, post - advanced gas injection, the test area’s central old well A0XX rose from 1.1t/d before shutdown to 16.2t/d. Production wells with only middle and lower reservoir perforation had an initial maximum output 2.5 times that of wells with full reservoir perforation. Advanced CO2 injection has begun to boost production effectively.

Cyclic solvent injection (CSI) with CO2 is a promising non-thermal enhanced oil recovery (EOR) method for heavy oil reservoirs that also supports CO2 sequestration. However, its effectiveness is limited by short foamy oil flow durations and low CO2 utilization. This study explores how waterflooding and nanoparticle-assisted flooding can enhance CO2-CSI performance through experimental and numerical approaches. Three sandpack experiments were conducted: (1) a baseline CO2-CSI process, (2) a waterflood-assisted CSI process, and (3) a hybrid sequence integrating CSI, waterflooding, and nanoparticle flooding. The results show that waterflooding prior to CSI increased oil recovery from 30.9% to 38.9% under high-pressure conditions and from 26.9% to 28.8% under low pressure, while also extending production duration. When normalized to the oil saturation at the start of CSI, the Effective Recovery Index (ERI) increased significantly, confirming improved per-unit recovery efficiency, while nanoparticle flooding further contributed an additional 5.9% recovery by stabilizing CO2 foam. The CO2-CSI process achieved a maximum CO2 sequestration rate of up to 5.8% per cycle, which exhibited a positive correlation with oil production. Numerical simulation achieved satisfactory history matching and captured key trends such as changes in relative permeability and gas saturation. Overall, the integrated CSI strategy achieved a total oil recovery factor of approximately 70% and improved CO2 sequestration efficiency. This work demonstrates that combining waterflooding and nanoparticle injection with CO2-CSI can enhance both oil recovery and CO2 sequestration, offering a framework for optimizing low-carbon EOR processes.

No abstract available

Storing CO2 in deep saline aquifers is a key strategy for carbon capture and storage, an essential technology in the global effort to mitigate greenhouse gas emissions. Several mathematical and computational models have been proposed to simulate CO2 storage in geological formations [1-3]. These models aim to comprehensively capture the intricate interactions between fluids, gases, and geological media. In this study, we propose a novel quadrilateral finite element designed to simulate the flow of CO2 and water in an isothermal deformable porous medium. This element has been developed in user element subroutine (UEL) of Abaqus. The balance equations include momentum balance, as well as the mass balance of CO2 and water as outlined in prior research [2]. The proposed element is used to simulate certain tests, and preliminary results are presented.

The development of gas condensate fields under the conditions of elastic water drive is characterized by uneven movement of the gas-water. Factors of hydrocarbon recovery from producing reservoirs which are characterized by the active water pressure drive on the average make up 50-60%. To increase the efficiency of fields development, which are characterized by an elastic water drive, a study of the effect of different volumes of carbon dioxide injection at the gas-water contact on the activity of the water pressure system and the process of flooding producing wells was carried out. Using a three-dimensional model, the injection of carbon dioxide into wells located at the boundary of gas-water contact with flow rates from 20 to 500 thousand m3/day was investigated. Analyzing the simulation data, it was found that increasing the volume of carbon dioxide injection provides an increase in accumulated gas production and a significant reduction in water production. The main effect of the introduction of this technology is achieved by increasing the rate of carbon dioxide injection to 300 thousand m3/day. The set injection rates allowed us to increase gas production by 67% and reduce water production by 83.9% compared to the corresponding indicators without injection of carbon dioxide. Taking into account above- mentioned, the final decision on the introduction of carbon dioxide injection technology and optimal technological parameters of producing and injection wells operation should be made on the basis of a comprehensive technical and economic analysis using modern methods of the hydrodynamic modeling of reservoir systems.

The object of research is the processes of multiphase filtration in porous media. These processes occur when carbon dioxide (CO₂) is injected into oil reservoirs to increase oil recovery. The object is also the interphase phenomena, geochemical interactions and technological operations for well control associated with these processes. One of the most problematic areas is the lack of understanding of complex relationships. These relationships exist between physicochemical processes at the micro level (interfacial tension, wettability, solubility, adsorption, geochemical reactions) and macroscopic characteristics of the reservoir (permeability, porosity, heterogeneity). Technological parameters of CO₂ injection (pressure, temperature, speed, volume) are also important. This leads to suboptimal selection of technologies for increasing oil recovery technologies, premature CO₂ breakthroughs, low oil recovery ratios, and also complicates the prediction of the behavior of the “reservoir – fluid – CO₂” system in the long term, in particular, from the point of view of CO₂ storage safety. Another problematic area is the limitation of existing empirical models describing the impact of CO₂ injection on well productivity, which do not fully take into account the heterogeneity of the reservoir and the complexity of physicochemical processes. A comprehensive overview of the mechanisms of CO₂ interaction with reservoir fluids and rock has been obtained. The impact of supercritical CO₂ on interfacial tension, wettability, swelling and viscosity of oil has been analyzed. Geochemical reactions and their impact on permeability have been considered. CO₂ mobility control has been investigated. Mathematical relations for the calculation of throttling devices have been developed. An analysis of industrial data has been conducted, which revealed a nonlinear response of wells and allowed to refine regression models. This provides the possibility of obtaining increased oil recovery rates and long-term CO₂ binding. Compared with similar known methods, CO₂ provides a decrease in interfacial tension, a decrease in oil viscosity, dissolution of residual oil and a potential reduction in greenhouse gas emissions. Refined regression models allow for a more accurate prediction of well productivity. The developed mathematical relationships provide effective well management. The results obtained can be used in practice to optimize oil field development processes using CO₂ injection technologies, as well as to assess and ensure the safety of long-term CO₂ storage in geological formations.

CO2 possesses several advantages, including strong solubility, effective viscosity reduction ability, and low miscible pressure, making it a promising candidate for enhanced oil recovery (EOR). Additionally, due to its adsorption capture mechanism, shale formations are considered ideal environments for CO2 storage. However, the influence of heterogeneity of shale multi-scale structure on CO2 migration mechanism, EOR, and storage mechanism is not clear. In this study, a heterogeneous shale structure model containing fractures and matrix was designed based on scanning electron microscope. The multiphase–multicomponent–multirelaxation model was used to study the fluid migration mechanism in the process of miscible CO2 huff-n-puff in shale reservoir. By analyzing density variations, velocity changes, and pressure distributions, the effects of diffusion coefficient, adsorption parameters, and fracture size were studied. Furthermore, by changing the matrix structure, the influence of heterogeneity on the law of oil and gas migration was explored. Additionally, a comparison between CO2 and water was performed. Finally, the influence of reservoir heterogeneity on fluid transport mechanism was studied. The results show that EOR and CO2 storage rate (CSR) are proportional to the diffusion coefficient. The main factor affecting the CSR is the adsorption capacity of rock to CO2. The larger CO2–oil contact area between the fracture and the matrix leads to a larger CSR, highlighting the importance of induced fractures. In addition, it was found that CO2 huff-n-puff was superior to water flooding, showing an EOR performance advantage of about 15%. This study is helpful for the practical application of CO2 huff-n-puff technology in the field of unconventional oil and gas development and CO2 storage.

This study examines the impact of hysteresis effects on oil recovery during CO₂-Water Alternating Gas (WAG) injection, a widely applied enhanced oil recovery (EOR) technique with significant implications for carbon capture, utilization, and storage (CCUS). Hysteresis, which describes the cyclic variations in relative permeability during alternating imbibition and drainage cycles, plays a critical role in accurately modeling multiphase flow in porous media. However, its effects on CO₂-WAG efficiency remain underexplored in many reservoir simulations. To address this gap, a sector model was developed to simulate CO₂- WAG injection, incorporating hysteresis effects to assess their influence on oil recovery and CO₂ trapping. The results reveal that considering hysteresis leads to a 0.9% increase in the oil recovery factor, demonstrating its role in enhancing residual oil mobilization. Moreover, hysteresis significantly contributes to greater CO₂ retention within the reservoir, improving long-term sequestration potential and reducing gas production rates. The findings underscore the necessity of incorporating hysteresis in CO₂-WAG simulations to improve the accuracy of EOR performance predictions and optimize CCUS strategies. Neglecting hysteresis can lead to an underestimation of both oil recovery and CO₂ trapping potential, impacting reservoir management decisions. This study highlights the importance of precise relative permeability modeling in CO₂-WAG injection to ensure reliable performance forecasts and efficient field implementation.

In recent years, CO2 flooding has become an important technical measure for oil and gas field enterprises to further improve oil and gas recovery and achieve the goal of “dual carbon”. It is also one of the concrete application forms of CCUS. Numerical simulation based on CO2-EOR plays an indispensable role in the study of the mechanism of CO2 flooding and buried percolation, allowing for technical indicators to be selected and EOR/EGR prediction to be improved for reservoir engineers. This paper discusses the numerical simulation techniques related to CO2 flooding and storage, including mathematical models and solving algorithms. A multiphase and multicomponent mathematical model is developed to describe the flow mechanism of hydrocarbon components–CO2–water underground and to simulate the phase diagram of the components. The two-phase P-T flash calculation with SSI (+DEM) and the Newton method is adopted to obtain the gas–liquid phase equilibrium parameters. The extreme value judgment of the TPD function is used to form the phase stability test and miscibility identification model. A tailor-made multistage preconditioner is built to solve the linear equation of the strong-coupled, multiphase, multicomponent reservoir simulation, which includes the variables of pressure, saturation, and composition. The multistage preconditioner improves the computational efficiency significantly. A numerical simulation of CO2 injection in a carbonate reservoir in the Middle East shows that it is effective for researching the recovery factor and storage quantity of CO2 flooding based on the above numerical simulation techniques.

The stability of the gas displacing oil front (i.e., gas–oil interface) is of the utmost importance for the success of the immiscible gas flooding project under crestal gas injection. However, the preceding gas flooding assessment models are deficient in their description of the gas flooding mechanism, and they do not take into account the critical influencing factors in a comprehensive manner. Utilizing theoretical derivation, oilfield justifications, criterion and experiment validation, and dimensional analysis on crestal gas injection for stable flooding, this study presents an innovative theory and technique for artificial CO2 gas cap immiscible rigid stable gas flooding under CO2 injection, which could not only greatly improve crude oil recovery but also realize CO2 geological storage on a large scale, and new insights into displacement mechanism on the gas–oil interface through artificial CO2 gas cap immiscible rigid stable gas flooding process. Based on the multiphase filtrate theory, considering the influencing factors such as crude oil density, crude oil viscosity, density of injected gas, gas injection rate, strata dip, liquid phase relative permeability, air permeability in formation direction, viscosity of injected gas, gas phase relative permeability and the acting forces such as buoyancy, gravity, driving pressure, capillary pressure, viscous force and additional resistance in multiphase flow during the artificial CO2 gas cap immiscible rigid stable gas flooding process under CO2 injection, A simple quantified artificial CO2 gas cap immiscible rigid stable gas flooding assessment model (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${N_{{\text{GOI}}}}$$\end{document}) was established. The results indicate the artificial CO2 gas cap immiscible rigid stable gas flooding process has the theory and field feasibility of greatly enhancing crude oil recovery and realizing CO2 geological storage on a large scale. And the oil reservoirs with strata dip, which have large oil and gas density difference, small oil and gas viscosity ratio, large oil and gas relative permeability ratio, large strata dip, and large air permeability in the direction are easy to exert gravity and buoyancy, reduce the influence of capillary pressure, viscosity and additional resistance, benefit to maintain the stability of gas displacing oil front and improve microscopic oil displacement efficiency, and facilitate the implementation of artificial CO2 gas cap immiscible rigid stable gas flooding development. In addition, the theoretical deduction, field and experimental validation indicate that artificial CO2 gas cap immiscible rigid stable gas flooding under CO2 injection can be realized when \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${N_{{\text{GOI}}}}$$\end{document} is greater than 1. The proposed \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${N_{{\text{GOI}}}}$$\end{document} model can be used as a creterion to assess the stablity and efficiency of the crestal gas injection for stable flooding such as artificial CO2 gas cap immiscible rigid stable gas flooding, artificial CO2 gas cap immiscible stable gas flooding, GAGD, gravity assisted gas injection, and crestal gas injection for stable gravity flooding for theoretical investigation, numerical simulation, laboratory test and field trial project design or operation.

The CO2-enhanced oil recovery (CO2-EOR) technique could increase the oil recovery factor and achieve subsurface CO2 storage. To evaluate the feasibility of CO2-EOR operation, an equation-of-state-based (EOS-based) compositional simulation is inevitable. However, time-consuming multiphase flash calculations limit the application of the conventional EOS-based compositional simulation in large-scale reservoir simulations. Therefore, there is an urgent need to accelerate the EOS-based compositional simulation by reducing the time spent on the multiphase flash calculations. In this study, we develop a fast, multiphase-state identification approach to achieve high computational efficiency of the compositional simulation. First, taking one given point in the compositional space composed by pressure and the overall composition as the original point, the phase-state radius (PSR) is defined as a radius inside which all points have the same phase state as the given point. Subsequently, the results of the multiphase flash calculations of the points in the compositional space are stored. Finally, when a new point is inside the PSR of one calculated point, the stored results are used to accelerate the new multiphase flash calculations of the new point by omitting the phase stability analysis (PSA) and possible additional multiphase split (MS) calculations. Case studies show a 6–10% reduction in multiphase flash computation time compared with two existing methods when the fluid is far from the phase boundary and a reduction of at least 17.5% when the fluid is near the phase boundary.

No abstract available

Under the globally advocated initiative of carbon capture, utilization, and storage, CO2-enhanced oil recovery has emerged as the preferred injection strategy for tight or shale oil reservoirs. The CO2–oil–water interactions induce complex multiphase behavior in reservoirs, yet previous studies regarded the aqueous phase as an inert phase, largely neglecting or underestimating its impact on CO2–oil systems. This study designed and conducted pressure–volume–temperature cross-experiments with varying CO2-to-water ratios to simulate reservoir multiphase conditions, elucidating aqueous phase effects on CO2–oil systems by phase behavior perspective. The phase behavior modeling of water-bearing CO2–oil systems was achieved by coupling the Soave–Redlich–Kwong equation of state (SRK EOS) with the Cubic Plus Association (CPA) term and Huron–Vidal (H–V) mixing rules. The results show that the SRK-CPA EOS model achieves satisfactory accuracy in describing the phase behavior of water-bearing oil systems compared to the classical SRK EOS. CO2 injection exhibits greater potential for viscosity reduction due to its higher solubility. However, this mechanism is suppressed when the aqueous phase is considered due to the partitioning dissolution of CO2 in water. In CO2–oil–water systems, a rising water cut weakens CO2's viscosity-reducing effect, simultaneously resulting in greater solubility loss in water compared to CH4, a more pronounced decline in the three-phase hydrocarbon boundary line, and contraction of the three-phase region in the phase envelope. In contrast, the two-phase hydrocarbon boundary line contracts inward, which is completely opposite to that observed in oil–water systems in previous experiments. Finally, the critical water saturation threshold can be quantified by analyzing the rate of change in key parameters, such as saturation pressure. The findings of this study provide valuable insights for evaluating multiphase behavior, CO2 storage potential, injection parameter optimization, and solubility loss in water-bearing reservoirs during CO2 flooding.

Carbon dioxide (CO2) injection effectively enhances oil recovery from shale reservoirs while potentially storing CO2. Several operational and reservoir parameters impact the oil recovery factor and CO2 storage efficiency. Rather than conducting extensive simulations through sensitivity analysis, dimensional analysis offers valuable insights into the dominant parameters affecting the incremental recovery factor (IRF) and CO2 storage efficiency (EF). Accordingly, we conduct a dimensional analysis of CO2 injection in shale reservoirs by defining the key dimensionless parameters, including Fourier number (Fo), diffusivity ratio (RD), and drawdown pressure (PD). We then use a multiphase, multicomponent transport model that accounts for molecular diffusion, Knudsen diffusion, and viscous flow to simulate a single cycle of the cyclic CO2 injection process at different operational and reservoir conditions. Using the simulation results, we investigate the scaling relations between key dimensionless parameters (Fo, RD, and PD) and IRF and EF. The results indicate that, IRF increases with Fo and reaches a plateau (maximum IRF) at an optimal Fo, like Fo = 0.006 at PD = 0.25 and 0.5. Beyond this point, the effect of diffusion on IRF becomes negligible. This suggests that the pressure gradient becomes the dominant recovery mechanism, particularly after the IRF reaches a plateau, where the effect of diffusion is minimal. In addition, RD shows a positive correlation with IRF, indicating that diffusion during the soak period has a favorable impact on oil recovery. In contrast, RD has little influence on EF. The relationship between Fo and EF is similar to that of Fo and IRF, where higher IRF values correspond to greater pore space available for CO2 storage due to increased oil production. This relationship highlights the dual benefit of enhanced oil recovery and CO2 sequestration, which can be better understood and optimized through the presented dimensional analysis.

In CO2-enhanced oil recovery (EOR) and geological sequestration processes, multiphase flow mechanisms play a critical role in controlling both displacement efficiency and CO2 storage security. In this study, a high-temperature, high-pressure microfluidic platform was employed to investigate pore-scale flow mechanisms and residual shale oil trapping during water and supercritical CO2 (scCO2) immiscible flooding. The K-means clustering algorithm was employed to quantitatively characterize fluid saturations. Furthermore, high-magnification Zeiss microscopy was utilized to identify residual oil trapping types and elucidate their formation mechanisms at the pore scale. The results indicate that during scCO2 flooding, capillary fingering and Haines jumps are pronounced. As the capillary number increases, the capillary fingering effect diminishes while CO2 channeling becomes increasingly pronounced; in contrast, capillary fingering is relatively weak during water flooding and at higher capillary numbers, residual oil initially transforms into small-scale columnar forms. These findings advance the fundamental understanding of multiphase flow and residual oil trapping in unconventional reservoirs and provide essential theoretical guidance for optimizing CO2-EOR strategies and improving the efficiency of geological CO2 storage.

Fluid-fluid interfacial reactions in porous materials are pertinent to many engineering applications such as fuel cells, catalyst design, subsurface energy recovery (enhanced oil recovery), and CO2 storage. They have been identified to control physicochemical properties such as interfacial rheology, multiphase flow, and reaction kinetics. In recent years, engineered waterflooding has been identified as an effective way to increase hydrocarbon recovery and solid-fluid interaction has been assessed as the key mechanism. However, in this study, we demonstrated that in the absence of solid-fluid interactions (in strong hydrophilic porous media), fluid-fluid interfacial reactions can significantly affect multiphase flow and thus lead to an increased hydrocarbon recovery during engineered carbonated waterflooding. We designed a microwaterflooding system to evaluate the interfacial reactions during two phase flow with engineered carbonated waters. Given that salinity controls the amount of dissolved CO2, we injected carbonated high salinity water and carbonated low salinity water to achieve different fluid-fluid reactions. We injected the carbonated water in a sandstone with 99.5% quartz under X-ray microcomputed tomography (μCT) scanning at a resolution of 3.43 μm per pixel. Image processing shows that carbonated low salinity waterflooding can recover 8% more oil than carbonated high salinity waterflooding, while the quartz-rich sandstone remains strongly hydrophilic in both samples. A gradual CT intensity distribution indicates an interfacial phase generation between carbonated brine and crude oil during carbonated waterflooding. Therefore, we attributed the additional hydrocarbon recoveries to the fluid-fluid interfacial reactions. To understand the effects of fluid-fluid reactions on interfacial properties, we performed molecular dynamics simulations to investigate the chemical species distribution at the interface, interfacial tension (IFT) changes, and CO2 diffusion. The MD simulation results revealed a layered structure of the interface, a lower CO2 diffusion coefficient in carbonated high salinity water, a lower IFT in carbonated low salinity water, a swelling hydrocarbon phase in carbonated low salinity water, and more CO2 accumulated at the interface between the hydrocarbon phase and carbonated low salinity water. This work provides a general and fundamental understanding of the influence of fluid-fluid interactions on the interfacial properties between carbonated water and the hydrocarbon interface.

Pressure limitations of many microfluidic platforms have been a significant challenge in microfluidic experimental studies of fractured media. As a result, these platforms have not been fully exploited for direct observation of high-pressure transport in fractures. This work introduces microfluidic platforms that enable direct observation of multiphase flow in devices featuring surrogate permeable media and fractured systems. Such platforms provide a pathway to address important and timely questions such as those related to CO2 capture, utilization and storage. This work provides a detailed description of the fabrication techniques and an experimental setup that may serve to analyze the behavior of supercritical CO2 (scCO2) foam, its structure and stability. Such studies provide important insights regarding enhanced oil recovery processes and the role of hydraulic fractures in resource recovery from unconventional reservoirs. This work presents a comparative study of microfluidic devices developed using two different techniques: photolithography/wet-etching/thermal-bonding versus Selective Laser-induced Etching. Both techniques result in devices that are chemically and physically resistant and tolerant of high pressure and temperature conditions that correspond to subsurface systems of interest. Both techniques provide pathways to high-precision etched microchannels and capable lab-on-chip devices. Photolithography/wet-etching, however, enables fabrication of complex channel networks with complex geometries, which would be a challenging task for laser etching techniques. This work summarizes a step-by-step photolithography, wet-etching and glass thermal-bonding protocol and, presents representative observations of foam transport with relevance to oil recovery from unconventional tight and shale formations. Finally, this work describes the use of a high-resolution monochromatic sensor to observe scCO2 foam behavior where the entirety of the permeable medium is observed simultaneously while preserving the resolution needed to resolve features as small as 10 µm.

As the world transitions toward net-zero emissions, integrating carbon capture and utilization strategies into petroleum production processes is essential for reducing carbon intensity. This study investigates the potential of combined CO₂-enhanced oil recovery (CO₂-EOR) and storage within the residual oil zones (ROZ) of the Wall Creek Formation in Wyoming's Powder River Basin. Multi-phase core flooding experiments were conducted to evaluate CO₂ performance in terms of oil recovery and storage capacity across various sandstone facies. The experiments utilized core samples representative of the basin's depositional environments and involved measuring fluid properties, relative permeability, and recovery factors under reservoir conditions. Results indicate that medium-grained distributary complex sandstones exhibit superior permeability and recovery efficiency, achieving up to 68.7% recovery and 28.8% CO₂ storage potential. Comparatively, tidal shoal facies demonstrated lower recovery and storage capacities due to finer grain size and reduced permeability. These findings underscore the viability of optimized CO₂-EOR and storage in sandstone ROZ fairways, advancing the understanding of subsurface carbon storage in challenging clastic reservoirs

To optimize enhanced oil recovery (EOR) techniques for pre-fractured heavy oil reservoirs, this research conducted long-core flooding experiments using three distinct injection media: CO2, water, and CO2/water alternate huff-n-puff. A 35 cm composite core was employed to simulate the reservoir conditions after pre-fracturing. Experimental results indicated that the CO2 huff-n-puff process yielded the highest oil production, enhancing the overall recovery factor by 33.0% compared to depletion production, with a total recovery factor of 43.8% after four optimized cycles. The CO2/water alternate huff-n-puff process increased the recovery factor by 28.3%, achieving a total of 41.9% after four cycles. In contrast, water injection improved the recovery factor by only 15.2%, reaching a total of 26.2% after three cycles. By evaluating both oil recovery efficiency and oil exchange ratio, the optimal cycle numbers were determined as four cycles for CO2 huff-n-puff, four cycles for CO2/water alternate huff-n-puff, and three cycles for water huff-n-puff. Based on these optimized parameters, the CO2/water alternate huff-n-puff process was identified as the most effective EOR method for the target reservoir. Furthermore, this study assessed the potential for CO2 storage in the reservoir post-production. Calculations of CO2 storage ratios during the huff-n-puff process demonstrated the feasibility of integrating enhanced oil recovery with carbon sequestration. The findings provide a practical strategy for improving heavy oil recovery in low-permeability reservoirs while concurrently exploring the benefits of CO2 storage.

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Egypt formulated its sustainable development strategy "Egypt Vision 2030" in 2015. This strategy aims to protect the environment in the development process by integrating environmental aspects into economic and social development plans to manage natural resources, conserve natural capital, and develop to protect the environmental rights of future generations. According to the IEA (International Energy Agency) CO2 emission reduction projects to track advances in carbon capture, utilization, storage as well as use of naturally occurring CO2 for EOR (Enhanced Oil Recovery) of depleted reservoirs. This paper proposes a methodology for evaluating underground CO2 storage capacity according to the facies of different formations applicable to the CO2 EOR projects. The methods proposed in this document will not only help third parties create reports and inventories of greenhouse gas emissions from companies, but also help governments to encourage companies to reduce their CO2 emissions. It would be beneficial for the industry implementing CCUS (Carbo Capture Utilize and Storage) projects to provide key evaluation parameters and implement the necessary monitoring techniques. Due to advantages and vast resource capacity, onshore CO2 storage provides an attractive option. Bahariya concession is located at the eastern trough of Abu Gharadig basin, Western Desert, Egypt. By Using the available data, a subsurface geologic evaluation and 3D modelling was carried out in terms of thickness variation, lithofacies, structural setting and depositional environment of the studied rock unit in the encountered basin. This study presents both depleted reservoir and shallow non-reservoir formations as preliminary targets for CO2 storage potential. It was concluded that both clastic and non-clastic Cretaceous formations have a high-quality potential geological reservoir repository for CO2 storage capacity.

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Carbon Capture, Utilization, and Storage (CCUS) through CO2 Enhanced Oil Recovery (CO2-EOR) supports energy production while reducing atmospheric CO2 emissions. Economic profitability, not environmental

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Carbon capture, utilization and sequestration (CCUS) is one of the most promising and effective technologies to reduce carbon emissions, with significant potential for development in the coming decades. The CCUS coupling project utilizing CO2 Enhanced Oil Recovery (CO2-EOR) can pave the way to economically viable CO2 sequestration processes. However, the non-linear and non-convex relationships among CO2 sequestration capacity, CO2-EOR effectiveness, and economic benefits significantly increase uncertainty in technological policy formulation. This paper establishes a comprehensive optimization framework utilizing the Particle Swarm Optimization (PSO) algorithm, encompassing the formulation of objective functions, the development of numerical simulation models for typical reservoirs, and single-objective and multi-objective optimization method. In single-objective optimization, two objective functions—oil recovery factor and CO2 sequestration efficiency—are accomplished through weight assignment. This approach optimizes the combined objective function across different injection modes, including Continuous gas injection (CGI), Water-alternating-gas (WAG), and Gas injection after water flooding (GIW), while also considering diverse preferences for development strategies. In multi-objective optimization, the optimal well control parameter sets for CO2 sequestration and Net Present Value (NPV) are derived under different injection modes using Multi-Objective Particle Swarm Optimization (MOPSO) algorithm and the Pareto front. The results indicate that the multi-objective optimization method constructed in this paper can effectively address the problem of Co-Optimization of CO2-EOR projects. Compared to the base scenario and the single-objective optimization, the MOPSO optimization solutions on the Pareto front demonstrate superior overall performance in terms of oil recovery, sequestration capacity, and economic benefits through reasonable injection and production parameters that control the CO2 flooding front and expand the sweep efficiency. Water-Alternating-Gas (WAG) exhibits advantages in recovery rate and NPV while demonstrating lower sensitivity to carbon subsidies and CO2 injection costs. The comprehensive optimization method proposed in this paper will significantly enhance the technical decision-making capabilities related to CCUS coupling projects in carbonate reservoirs, providing guidance for safe and efficient CCUS technologies.

The dual imperative of mitigating carbon emissions and maximizing hydrocarbon recovery has amplified global interest in carbon capture, utilization, and storage (CCUS) technologies. These integrated processes hold significant promise for achieving net-zero targets while extending the productive life of mature oil reservoirs. However, their effectiveness hinges on a nuanced understanding of the complex interactions between geological formations, reservoir characteristics, and injection strategies. In this study, a comprehensive machine learning-based framework is presented for estimating CO2 storage capacity and enhanced oil recovery (EOR) performance simultaneously in subsurface reservoirs. The methodology combines simulation-driven uncertainty quantification with supervised machine learning to develop predictive surrogate models. Simulation results were used to generate a diverse dataset of reservoir and operational parameters, which served as inputs for training and testing three machine learning models: Random Forest, Extreme Gradient Boosting (XGBoost), and Artificial Neural Networks (ANN). The models were trained to predict three key performance indicators (KPIs): cumulative oil production (bbl), oil recovery factor (%), and CO2 sequestration volume (SCF). All three models exhibited exceptional predictive accuracy, achieving coefficients of determination (R2) greater than 0.999 across both training and testing datasets for all KPIs. Specifically, the Random Forest and XGBoost models consistently outperformed the ANN model in terms of generalization, particularly for CO2 sequestration volume predictions. These results underscore the robustness and reliability of machine learning models for evaluating and forecasting the performance of CO2-EOR and sequestration strategies. To enhance model interpretability and support decision-making, SHapley Additive exPlanations (SHAP) analysis was applied. SHAP, grounded in cooperative game theory, offers a model-agnostic approach to feature attribution by assigning an importance value to each input parameter for a given prediction. The SHAP results provided transparent and quantifiable insights into how geological and operational features such as porosity, injection rate, water production rate, pressure, etc., affect key output metrics. Overall, this study demonstrates that integrating machine learning with domain-specific simulation data offers a scalable approach for optimizing CCUS operations. The insights derived from the predictive models and SHAP analysis can inform strategic planning, reduce operational uncertainty, and support more sustainable oilfield development practices.

CO2 injection can enhance oil recovery and achieve geological carbon sequestration. The miscibility between CO2 and crude oil significantly impacts the CO2 EOR performance. Although the minimum miscible pressure (MMP) can be obtained by slim-tube experiment or slim-tube modeling, it is time-consuming, inconvenient, and complicated. This work aims to enhance the prediction efficiency and accuracy of MMP between CO2 and crude oil under reservoir conditions by improved and integrated machine-learning approaches. A novel method is proposed to improve the forecasting accuracy and efficiency of the MMP by integrating Grey Wolf optimization (GWO) and improved GWO (IGWO) into the Support Vector Machine (SVM) algorithm. Firstly, data sets are collected and data preprocessing is performed to improve the quality of data sets. Secondly, K-fold cross-validation is applied to enhance the generalization of the model. The MMP is predicted by the SVM algorithm. Thirdly, the MMP prediction can be enhanced by introducing GWO and IGWO algorithms, and the optimal model is investigated to evaluate the effect and convergence of the SVM-GWO and SVM-IGWO algorithms. Fourthly, the predicted MMP and evaluation index (MAE, MAPE) are compared. Finally, the field case study is performed to show the practical potential of the approach. The dominant factors of the MMP include formation temperature (TR), MwC5+ (Molecular weight of pentane plus), MwC7+ (Molecular weight of heptane plus), Volatile (mole fraction of volatile components including N2 and CH4), and Intermediate (mole fraction of intermediate components including CO2, H2S, and C2–C4). The data set is formed by filling 87 groups of missing values using the K-Nearest Neighbor (KNN) algorithm and removing 19 groups of outliers based on the Box-plot detection method. The accuracy is improved by 37.45% and 40.79% using GWO and IGWO based on the MAE compared to SVM. The calculated MAPE shows that the accuracy can be enhanced by 37.79% and 41.29% after adding GWO and IGWO. The SVM-GWO and SVM-IGWO improved the accuracy by 54.16% and 57.12%. The proposed method can accurately determine the MMP between CO2 and crude oil. The field case study highlights the reliability of the proposed method. The developed method can forecast the MMP between CO2 and crude oil more efficiently and economically.

This study focuses on carbon capture, utilization, and sequestration (CCUS) via the means of nonlinearly constrained production optimization workflow for a CO2-EOR process, in which both the net present value (NPV) and the net present carbon tax credits (NPCTC) are bi-objectively maximized, with the emphasis on the consideration of injection bottomhole pressure (IBHP) constraints on the injectors, in addition to field liquid production rate (FLPR) and field water production rate (FLWR), to ensure the integrity of the formation and to prevent any potential damage during life-cycle injection/production process. The main optimization framework used in this work is a lexicographic method based on line-search sequential quadratic programming (LS-SQP) coupled with stochastic simplex approximate gradients (StoSAG). We demonstrate the performance of the optimization algorithm and results in a field-scale realistic problem, simulated using a commercial compositional reservoir simulator. Results show that the workflow is capable of solving the single-objective and bi-objective optimization problems computationally efficiently and effectively, especially in handling and honoring nonlinear state constraints imposed onto the problem. Various numerical settings have been experimented with to estimate the Pareto front for the bi-objective optimization problem, showing the trade-off between the two objectives NPV and NPCTC. We also perform a single-objective optimization on the total life-cycle cash flow, which is the aggregated quantity of NPV and NPCTC, and quantify the results to further emphasize the necessity of performing bi-objective production optimization, especially when utilized in conjunction with commercial flow simulators that lack the capability of computing adjoint-based gradients.

Enhanced oil recovery (EOR) strategies, particularly CO2 flooding, play a crucial role in optimizing oil reservoir exploitation while addressing carbon sequestration. Despite their effectiveness, the application of these techniques is often hindered by complex reservoir dynamics and the computational intensity of traditional simulation models. This study introduces a novel approach utilizing the FlowNet model, which combines data-driven analytics and physics-based modeling, aimed at expediting history matching and production optimization processes. The FlowNet model simplifies the representation of reservoirs by using virtual well points along flow paths and employs a non-linear solver for quick resolution of flow equations. Our method significantly enhances the efficiency of history matching by reducing computational overheads and leveraging streamlined network structures, thereby facilitating faster and more accurate production forecasts. We implement the model in several case studies involving CO2 and water alternating gas flooding, which demonstrate an 11% increase in the economic net present value compared to traditional methods. These findings highlight the potential of integrating data-driven techniques with physical modeling to improve EOR performance predictions and optimize production strategies, ultimately promoting more sustainable and economically viable oil recovery practices.

In recent years, shale and tight reservoirs have become an essential source of hydrocarbon production since advanced multistage and horizontal drilling techniques were developed. Tight oil reservoirs contain huge oil reserves but suffer from low recovery factors. For tight oil reservoirs, CO2-water alternating gas (CO2-WAG) is one of the preferred tertiary methods to enhance the overall cumulative oil production while also sequestering significant amounts of injected CO2. However, the evaluation of CO2-WAG is strongly dependent on the injection parameters, which renders numerical simulations computationally expensive. In this study, a novel approach has been developed that utilized machine learning (ML)-assisted computational workflow in optimizing a CO2-WAG project for a low-permeability oil reservoir considering both hydrocarbon recovery and CO2 storage efficacies. To make the predictive model more robust, two distinct proxy models—multilayered neural network (MLNN) models coupled with particle swarm optimization (PSO) and genetic algorithms (GAs)—were trained and optimized to forecast the cumulative oil production and CO2 storage. Later, the optimized results from the two algorithms were compared. The optimized workflow was used to maximize the predefined objective function. For this purpose, a field-scaled numerical simulation model of the Changqing Huang 3 tight oil reservoir was constructed. By December 2060, the base case predicts a cumulative oil production of 0.368 million barrels (MMbbl) of oil, while the MLNN-PSO and MLNN-GA forecast 0.389 MMbbl and 0.385 MMbbl, respectively. As compared with the base case (USD 150.5 million), MLNN-PSO and MLNN-GA predicted a further increase in the oil recovery factor by USD 159.2 million and USD 157.6 million, respectively. In addition, the base case predicts a CO2 storage amount of 1.09×105 tons, whereas the estimates from MLNN-PSO and MLNN-GA are 1.26×105 tons and 1.21×105 tons, respectively. Compared with the base case, CO2 storage for the MLNN-PSO and MLNN-GA increased by 15.5% and 11%, respectively. In terms of the performance analysis of the two algorithms, both showed remarkable performance. PSO-developed proxies were 16 times faster and GA proxies were 10 times faster as compared with the reservoir simulation in finding the optimal solution. The developed optimization workflow is extremely efficient and computationally robust. The experiences and lessons will provide valuable insights into the decision-making process and in optimizing the Changqing Huang 3 low-permeability oil reservoir.

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CO2 injection has emerged as a pivotal technique in the petroleum industry, offering a cost-effective option to enhance oil recovery while contributing to improved environmental sustainability. The mass transfer of CO2 into reservoir fluids is the primary mechanism responsible for CO2 solubility trapping and enhancement of oil recovery. The minimum miscibility pressure between CO2 and crude oils controls the performance of any CO2-enhanced oil recovery (EOR) and storage project. This paper investigates the influence of reservoir conditions on the CO2-oil miscibility during CO2 injection in oil reservoirs. To do so, pendant drop tests were conducted, and CO2-oil interfacial tension (IFT) was measured at different pressures and two temperatures. The minimum miscibility pressure (MMP) and first contact miscibility pressure (FCM) between the CO2 and crude oil were estimated from the measured IFT values by applying the vanishing interfacial tension (VIT) technique. The measured MMP was found to increase with reservoir temperature as MMP increased from 1175 psi at T=27°C to 2007 psi at T=70°C. Similarly, the FCM pressure was found to significantly increase with reservoir temperature. This research provides a valuable guide for screening oil reservoirs suitable for EOR and CO2 storage.

Miscible gas injection is one of the promising methods to improve oil recovery. A CO2 gas injection pilot was successfully conducted in a highly complex heterogeneous reservoir in Indonesia. In this study, the result of the CO2 pilot test was used to find the optimum field development plan and address the key risk parameters. Compositional model of the field was validated using the latest production and pressure data. A recent pilot test has been accomplished as one of the early steps of field implementation of gas injection. Slim-tube simulation was carried out to compare the MMP against experimental measurement. Appropriate relative permeability curves were utilized to incorporate interfacial tension reduction due to miscibility. Then, sensitivity and optimization have been done to find the impact of operational parameters on oil recovery as the objective function. An AI-based proxy model was generated to relate influential parameters and the objective function and help us with risk mitigation. The field incorporates highly complex and heterogeneous formations and thus several modifiers besides local grids are applied in the model to describe the field performance. The recorded data during the pilot test were compared to the model results which exhibited high consistency. The estimated MMP from Slim-tube simulation was quite close to laboratory data. Some parameters such as pore volume injected, CO2 injection rate and Gas-oil ratio limit were included in the sensitivity parameters. Sobol analysis showed that maximum allowable GOR from operational point of view has the highest impact on objective function. Afterwards, response surface methodology (RSM) was applied to aid on building the proxy model. Different models were examined, and it was found that polynomial regression had the higher correlation factor of verification cases. Differential evolution methods have been applied to optimize oil production. The results showed that the oil recovery factor could be increased by 6% using miscible CO2 injection. Review of the model performance of injector well and nearby wells revealed that further improvement in oil recovery would be achieved by some squeezing and reperforation jobs of these wells. Results of this study will help to provide the roadmap and risk mitigation plan for CO2 field implementation by considering the operation issues including reservoir surveillance and flow assurance. Moreover, a comprehensive monitoring plan is suggested to integrate the well, reservoir and facilities which will assist to enhance the reservoir management and decision-making purposes.

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CO2-enhanced oil recovery (CO2-EOR) is widely used in reservoir development, but its implementation is often limited by scarce pure CO2 sources and high carbon capture costs. Flue gas from steam injection boilers typically contains 10-15% CO2 and 80-85% N2, both of which serve as effective gas displacement agents. Injecting flue gas or CO2/N2 mixtures into reservoirs can reduce carbon emissions, sequester CO2, and enhance recovery. Therefore, this study proposes a concept of enriching rather than capturing flue gas for storage, with a focus on how N2 as an impurity affects the safety of CO2 storage. This study examines interactions between gas mixtures with varying CO2 enrichment rates (with N2 impurities) and minerals. It performs microarea analyses of aged rocks using ultradepth-of-field microscope and atomic force microscopy (AFM), assesses calcite wettability via contact angle tests, and evaluates CO2 storage column height under experimental conditions. Results indicate that with a CO2 enrichment of at least 50%, adding N2 creates additional dissolution pits on calcite surfaces. The calcite matrix exhibits optimal water-wettability at 50-75% CO2 enrichment, facilitating greater CO2 storage column heights. This suggests coinjecting N2 and CO2 can enhance long-term CO2 storage safety and reduce capture costs.

This study investigates the combined effects of impurities in CO2 stream, geochemistry, water salinity, and wettability alteration on oil recovery and CO2 storage in carbonate reservoirs and optimizes injection strategy to maximize oil recovery and CO2 storage ratio. Specifically, it compares the performance of pure CO2 water-alternating gas (WAG), impure CO2-WAG, pure CO2 low-salinity water-alternating gas (LSWAG), and impure CO2-LSWAG injection methods from perspectives of enhanced oil recovery (EOR) and CO2 sequestration. CO2-enhanced oil recovery (CO2-EOR) is an effective way to extract residual oil. CO2 injection and WAG methods can improve displacement efficiency and sweep efficiency. However, CO2-EOR has less impact on the carbonate reservoir because of the complex pore structure and oil-wet surface. Low-salinity water injection (LSWI) and CO2 injection can affect the complex pore structure by geochemical reaction and wettability by a relative permeability curve shift from oil-wet to water-wet. The results from extensive compositional simulations show that CO2 injection into carbonate reservoirs increases the recovery factor compared with waterflooding, with pure CO2-WAG injection yielding higher recovery factor than impure CO2-WAG injection. Impurities in CO2 gas decrease the efficiency of CO2-EOR, reducing oil viscosity less and increasing interfacial tension (IFT) compared to pure CO2 injection, leading to gas channeling and reduced sweep efficiency. This results in lower oil recovery and lower storage efficiency compared to pure CO2. CO2-LSWAG results in the highest oil-recovery factor as surface changes. Geochemical reactions during CO2 injection also increase CO2 storage capacity and alter trapping mechanisms. This study demonstrates that the use of impure CO2-LSWAG injection leads to improved oil recovery and CO2 storage compared to pure CO2-WAG injection. It reveals that wettability alteration plays a more significant role for oil recovery and geochemical reaction plays crucial role in CO2 storage than CO2 purity. According to optimization, the greater the injection of gas and water, the higher the oil recovery, while the less gas and water injected, the higher the storage ratio, leading to improved storage efficiency. This research provides valuable insights into parameters and injection scenarios affecting enhanced oil recovery and CO2 storage in carbonate reservoirs.

Subsurface CO2 sequestration is a promising method to advance carbon neutrality and support the shift toward sustainable energy. However, the unique behavior of CO2 in these operations, particularly for cold CO2 injection in depleted hydrocarbon reservoirs, poses challenges to wellbore injectivity, reservoir containment, and reservoir capacity. These challenges necessitate the development of a numerical model to better understand and optimize the interplay between wellbore dynamics and reservoir processes. In this work, we present the development of an open-source coupled wellbore-reservoir numerical model, named DARTS-well, which is tailored to CO2 disposal in subsurface reservoirs. To this end, a multi-segment, multi-phase, non-isothermal wellbore model is first developed using the Drift-Flux Model (DFM), and its results for selected CO2 injection scenarios are validated against the commercial transient wellbore simulator OLGA. The multi-segment wellbore model is then coupled with the Delft Advanced Research Terra Simulator (DARTS) which is used in this study as the reservoir simulator. DARTS is widely used and validated for energy transition applications. The coupled model utilizes the Operator-Based Linearization (OBL) technique, employing state-dependent operators for thermodynamic properties interpolated from predefined tables or generated on the fly. This OBL parametrization approach addresses challenges associated with complex physics and reduces computational time, making it well-suited for modeling subsurface CO2 sequestration.

Carbon Capture, Utilization, and Storage (CCUS) technologies are pivotal in mitigating climate change by reducing CO₂ emissions from industrial sources. Among the most promising CCUS approaches is the integration of CO₂ sequestration with Enhanced Oil Recovery (EOR), which not only aids in reducing atmospheric CO₂ but also enhances hydrocarbon recovery from mature oil reservoirs. This evaluates hybrid CO₂ sequestration and EOR strategies, focusing on the optimization of CO₂ injection methods that maximize oil recovery while ensuring the long-term geological stability of the stored CO₂. CO₂ injection into oil reservoirs enhances oil recovery through mechanisms such as miscible displacement, oil viscosity reduction, and swelling effects. The study examines various CO₂ injection strategies, including continuous, cyclic, and water-alternating-gas (WAG) injection, and their effectiveness in improving oil recovery efficiency. Additionally, advanced methods like foam-assisted CO₂ injection are explored for their potential in increasing sweep efficiency and reducing CO₂ mobility, thus enhancing both hydrocarbon recovery and storage security. Ensuring the long-term stability of stored CO₂ is critical to the success of CCUS projects. The study assesses the factors influencing CO₂ retention, including capillary trapping, mineralization, and solubility trapping, and highlights the role of advanced monitoring techniques, such as 4D seismic imaging and pressure monitoring, to detect potential leakage and ensure the integrity of storage sites. This emphasizes the environmental and economic benefits of hybrid CCUS-EOR systems, which offer a dual advantage of climate change mitigation and extended hydrocarbon production. The review concludes with an analysis of the challenges and future directions for large-scale deployment, including technological advancements, cost barriers, and regulatory considerations, ultimately advocating for policy support and investment in CCUS technologies for sustainable energy production.

: Carbon dioxide capture and sequestration has attracted widespread interest worldwide due to greenhouse effect. Geological uncertainties affect final decisions of the injection work. Optimizing injection work under geological parameters can maximize the carbon dioxide injection efficiency and minimize the difference between the carbon dioxide storage target and actual injection volume. This work introduces an optimization workflow for decisions. It is composed of three steps. At first, generating samples as the initial data sets by using Latin Hypercube Sampling method. Secondly, a data-driven model is deployed to simulate the fluid movement in the reservoir using the samples generated in step 1. The surrogate model is optimized by tuning hyper parameters in neural networks and applying K-fold validation, which can mitigate the limitations of high-fidelity simulations. After optimization, the surrogate model is validated using full reservoir simulation. At last, with the help of genetic algorithm, both the critical pressure area and CO2 plume area reduce largely, and CO2 injection volume increases by 115*103 m3. This optimization can largely enhance CO2 sequestration efficiency. It introduces an efficient workflow to provide a reference to the decision-making process of CO2 injection location.

Carbon Capture and Storage (CCS) is a vital technology to reduce global CO2 emissions, which are expected to increase up to 40 gigatons per year by 2030, requiring new strategies to reach net-zero by 2050. The Cauvery Basin, an east coast of India Mesozoic- Cenozoic rift basin, is highly suitable for sequestration of CO2 with its 5–30% high-porosity sandstone reservoirs and permeability (10–1000 mD), but its multi-phase fault systems and stratigraphic complexity are difficult for conventional reservoir characterization. This research suggests an AI-based approach for reservoir characterization optimization for CO2 storage, leveraging the application of Convolutional Neural Networks (CNNs) for seismic interpretation, Machine Learning (ML) models for reservoir property prediction, and statistical verification for uncertainty assessment. The method utilizes a 1000-sample dataset of depth (500–3000 m), porosity, permeability, seismic amplitude (0.1–1.5), CO2 injection rate (100–500 kg/s), pressure (100–500 bar), and fault distance (0–1). 5-layer structured CNNs with Adam optimizer carry out the fault detection and facies classification automatically and minimize seismic misclassification error by 70% from the human approach, processing 1000 sections/hour. ML models—XGBoost, Random Forest, and MLP—tuned using PCA, RFE, and GridSearchCV forecast reservoir properties with XGBoost producing an RMSE of 0.0098 and R2 of 0.9871. Statistical validation in terms of Shapiro-Wilk tests, VIF analysis (e.g., VIF 6.03 for injection rate), and Pearson correlations confirms data integrity and model robustness. Results show 30% improvement in storage efficiency and 25% reduction in pressure buildup, with supporting residual error analysis. This approach avoids risks, including caprock failure, and enables real-time decision-making, which is in line with India's CCS aspirations. The future work will be expanded to Bayesian Neural Networks and GANs to further model uncertainty. This paper creates an extensible, data-driven benchmark for CCS, bridging the geophysical analysis-sustainable energy solution gap.

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The diffusion coefficient (DC) of CO2 in brine is a key parameter in geological carbon sequestration and CO2-Enhanced Oil Recovery (EOR), as it governs mass transfer efficiency and storage capacity. This study employs three machine learning (ML) models—Random Forest (RF), Gradient Boost Regressor (GBR), and Extreme Gradient Boosting (XGBoost)—to predict DC based on pressure, temperature, and salinity. The dataset, comprising 176 data points, spans pressures from 0.10 to 30.00 MPa, temperatures from 286.15 to 398.00 K, salinities from 0.00 to 6.76 mol/L, and DC values from 0.13 to 4.50 × 10−9 m2/s. The data was split into 80% for training and 20% for testing to ensure reliable model evaluation. Model performance was assessed using R2, RMSE, and MAE. The RF model demonstrated the best performance, with an R2 of 0.95, an RMSE of 0.03, and an MAE of 0.11 on the test set, indicating high predictive accuracy and generalization capability. In comparison, GBR achieved an R2 of 0.925, and XGBoost achieved an R2 of 0.91 on the test set. Feature importance analysis consistently identified temperature as the most influential factor, followed by salinity and pressure. This study highlights the potential of ML models for predicting CO2 diffusion in brine, providing a robust, data-driven framework for optimizing CO2-EOR processes and carbon storage strategies. The findings underscore the critical role of temperature in diffusion behavior, offering valuable insights for future modeling and operational applications.

Foam has been widely used for enhanced oil recovery (EOR) and CO2 sequestration due to its ability to improve sweep efficiency and control gas mobility. However, foam instability poses challenges for long-term applications. While nanoparticles have been explored as foam stabilizers, their high cost and limited availability hinder large-scale use. This study investigates red mud-derived nanoparticles (RMNPs), synthesized from industrial waste, as an affordable and sustainable alternative to traditional foam stabilizers. RMNPs were produced by ball milling at varying milling durations, achieving sizes below 200 nm. Characterization of the RMNPs was conducted using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), zeta potential measurements, and particle size analysis. Foaming solutions were prepared with alpha-olefin sulfonate (AOS) anionic surfactant, with and without the RMNPs, in deionized water, seawater, and brines (NaCl and CaCl2), covering pH 3–11. Foam stability was evaluated via handshake tests and dynamic foam analyses using nitrogen and carbon dioxide gases. Results showed that incorporating RMNPs significantly enhanced foam stability, increasing foam half-life by up to 60% with nitrogen and 57% with CO2. Nanoparticles milled for 30 h yielded optimal performance, forming fine and uniform bubble structures. Zeta potential analysis confirmed strong hydrophilic properties of the RMNPs, promoting stability in aqueous solutions. pH sensitivity tests indicated optimal stability at pH 4–5, while highly acidic conditions (pH 3) negatively affected stability. This work highlights the potential of red mud-derived nanoparticles as a low-cost stabilizer for foam applications in EOR and CO2 sequestration, supporting further optimization under reservoir conditions.