地球物理方向频率合并的期刊文献及实际分辨率提升效果

在分析常规利用RGB混频显示技术整合分频信号的应用效果及局限性基础上,提出将三参数小波频谱成像技术与信息融合技术结合应用来预测地质异常体空间展布的新方法。该方法首先构造三参数小波进行地震资料的频谱分解从而得到不同频率小波域的高精度地震信号。在此基础上利用基于模糊逻辑理论的信息融合算法来整合得到的分频信号,最终结果以概率的形式对地质异常体的展布特征进行精细定量刻画,实际资料的应用效果证明了该方法的有效性和实用性。

中国南海珠江口盆地潮汕凹陷中生界勘探面临地震波能量屏蔽严重、多次波发育等问题。本文借鉴宽线采集处理思路，对位置相近、两个年度采集的两条二维地震测线进行融合宽线处理研究，讨论处理中共深度点面元定义、多次波压制、成像方式等关键问题，开展噪声压制、多次波压制以及时差、振幅、频率、相位等的一致性处理，选用二维叠前深度偏移方法进行成像，取得良好处理效果。结果表明，进行融合宽线处理后，数据与原二维数据相比，中深层有效反射能量增强、频带拓宽、低频成分更加丰富、信噪比提高，多次波压制效果变好，速度分析准确性得以提升，目标层波组特征清晰且同相轴连续性变好。该方法为充分利用历史数据、提升中深层成像效果提供有益的借鉴，探索利用历史数据开展宽线处理的新方式，是一项在海上二维资料丰富区域开展中深层勘探的经济实用技术。

When multiple seismic surveys are acquired over the same area using different technologies that produce data with different frequency content, it may be beneficial to combine these data to produce a broader bandwidth volume. We propose a workflow for matching and blending seismic images obtained from shallow high-resolution seismic surveys and conventional surveys conducted over the same area. The workflow consists of three distinct steps: (a) balancing the amplitudes and frequency content of the two images by non-stationary smoothing of the high-resolution image; (b) estimating and removing variable time shifts between the two images; and (c) blending the two images together by least-squares inversion. The proposed workflow is applied successfully to images from the Gulf of Mexico.

… frequency range considerations, we perform a wavelet-based method to merge multiresolution seismic … with the high and very high resolution seismic sources of the SYSIF deep-towed …

“Spectral Fusion” is a new tool designed to combine different seismic datasets covering the same surveyed area, with<br>different but overlapping bandwidths resulting for instance from various source/receiver depths for marine streamer data. By<br>combining data with overlapping spectra a larger bandwidth can be recovered, with the benefit of using all of the available<br>information in the overlapping frequency domain without requiring any wave shaping or predefined filters, and therefore<br>better preserving the individual phase and amplitude character of the input data.

… traces are a common undesired characteristic caused by seismic data merging. … bandwidth and resolution. This study proposes a strategy for improving seismic resolution in general and …

Seismic blended source acquisition, also referred to as simultaneous source acquisition, is a cost‐effective technology that achieves a significant reduction in acquisition cycle time and increases seismic crew field productivity. The dispersed source array is a blended acquisition field technique that simultaneously employs sources emitting different types of sweeps (i.e. multi‐sweep), in terms of frequency bandwidth and length, which ultimately will result in a full broadband seismic data. In this paper, deblending of 3D multi‐sweep seismic blended data and the subsequent merging of the data volumes having different frequency bandwidths will be discussed. In specific data domains where the signal component is coherent, interference shots (i.e. blending noise) are randomly distributed in the data space according to its own shot firing time. Therefore, the deblending process, which separates interference shots from a signal component, becomes a noise attenuation problem. A sparse inversion methodology is applied in the frequency–wavenumber–wavenumber (f–kx–ky) domain to attenuate blending noise. By applying this deblending methodology to both dispersed source array's low‐ and mid‐high‐frequency bandwidths, we obtained high‐quality deblending results. For both frequency bandwidths of the deblended dispersed source array data, additional effort was made to combine the two datasets to a single broadband data volume. Consequently, deblending and merging of the dispersed source array blended data generated a broadband, deblended and well‐balanced seismic volume suitable for further processing and reservoir characterization applications.

… issues related to frequency, phase, energy and time differences in the merge processing on … frequency band and low main frequency of the original merged data lead to low-resolution …

… We evaluate these techniques in combination to assess their impact on frequency and amplitude distribution, seismic resolution enhancement, and interpretation of structural and …

During exploration, it is common to have access to multiple 3D post-stack seismic volumes, with different acquisition parameters, geometries and data quality that means conducting integrated interpretation and analyses of data between and across surveys can be challenging. Merging a 3D seismic survey would ideally require full re-processing using pre-stack data. However, given time, budgetary, data availability, or compute constraints, this is not always a practical solution. An alternative solution is to merge post-stack seismic volumes, which can provide a suitable substitute for many regional structural interpretation workflows. However, achieving a seamless post-stack seismic merge is challenging and often matching amplitudes, phase, and time shifts consistently cannot be done using bulk corrections across an entire survey due to lateral changes in geology. Seams at the boundaries between seismic surveys or changes in waveform characteristics will create challenges for interpretation, especially for the predictive tools being adopted for automated interpretation workflows. For example, a seam between two datasets is a large discontinuity that will lead to a potential false positive fault prediction. The seam may also prevent horizon interpretation tools from traversing between the two volumes. To reduce these challenges, we present an automated workflow for seamlessly merging two or more post-stack 3D seismic volumes that will enable easier interpretation workflows across regions where interpretations need to span multiple volumes. Traditionally, survey merging is achieved by applying seismic data interpolation/regularization, phase rotation, amplitude matches, and the optimal bulk time shift obtained to several seismic surveys to condition the different vintages and produce a seamless merged data set. This has been mainly done by designing a post-migration match filter which estimates wavelets in each time zone after isolating trace segments in the defined window and derived by least-squares time-domain with a smoothness constraint. However, after applying those estimated time, phase and amplitude adjustments, the surveys especially their spectra are matched in a loose sense. In case where the low frequency legacy data and high-resolution modern data are required to merge, the final spectrum is closer to low frequency spectrum of legacy data. The varying levels of resolution, acquisition patterns, and data quality in seismic surveys make their integration complex task. To overcome these challenges a mixture of selected deep-learning, optimization and classical machine-learning algorithms will be utilized to analyze and process data from multiple surveys. These algorithms will identify overlaps in the data and employ advanced techniques to match the spectra and phase of the seismic data, resulting in a seamless transition between different seismic surveys. Ultimately a complete merged 3D regional seismic survey will be generated. Various machine learning algorithms, including different types of neural networks will be utilized to analyze the data, detect gaps, and fill them with accurate data values.

With the continuous development of complex marine hydrocarbon reservoirs, broadband seismic data have shown growing advantages in revealing abundant stratigraphic information. Affected by acquisition conditions and stratigraphic attenuation, the acquired seismic data commonly suffer from narrow bandwidth, and conventional broadband processing techniques are incapable of optimizing the overall frequency band. This study proposes a coordinated high- and low-frequency broadband compensation method based on adaptive weight fusion to effectively extend the frequency bandwidth of seismic data. Firstly, wavefield separation is used to suppress ghost reflections, compensate low-frequency effective signals, and restore the continuity of the low-frequency spectrum. Then, based on the spectrum extrapolation method of maximum entropy spectrum estimation, a spectrum prediction model is established to achieve the continuation of high-frequency effective signals. Finally, in combination with the signal-to-noise ratio of each frequency band, the adaptive weight fusion algorithm is applied for weighted summation. The acquired broadband seismic data feature a continuous spectrum and balanced energy, greatly improving seismic imaging quality. Comparative results obtained using conventional processing methods verify that the proposed method can significantly improve stratigraphic continuity and wave group characteristics.

Abstract Understanding the hierarchical architectural elements of fluvial sand bodies is important for planning their development strategy and to enhance oil recovery. Red-Green-Blue (RGB) blending of multiple seismic attributes and forwarding seismic modelling are commonly used in the analysis of compound sand bodies. However, RGB blending of multiple seismic attributes can only qualitatively describe the boundaries and thickness of sand bodies. The forward seismic modelling techniques previously documented in the literature are not effective when depicting the geometry of, and stacking relationships between, sand bodies (i.e., reservoir compartmentalisation). Hence, we propose in this work a new workflow that combines fused spectral-decomposition seismic attributes (SDSAs) and forwarding seismic modelling to quantitatively predict sand thickness, and to characterise stacking relationships between sand bodies. First, we employ a Support Vector Machine (SVM) algorithm to fuse high, middle, and low frequency components (attributes) of seismic data so as to quantitatively predict the thickness of sand bodies. Second, we define the seismic waveform response patterns corresponding to the typical conceptual stacked sand bodies. With the constraints of waveform patterns and predicted sand thickness (fused SDSAs), the geometry and stacking relationships of the sand bodies are characterised by forward seismic modelling. To illustrate the effectiveness of our proposed workflow, we apply it to the Neogene Minghuazhen Formation (Nm) of the QHD 32–6 oil field, Bohai Bay Basin, China. We define five architectural elements of a meandering fluvial reservoir by analysing the hierarchy of sand bodies using our workflow. The predicted sand bodies in this workflow were further proven by horizontal drilling and production data.

… -based intelligent fusion approach for spectral-decomposed … reservoir prediction and seismic attributes fusion. The approach … the imaging characteristics of various spectral-decomposed …

Seismic attributes comprise an effective method for oil and gas reservoir characterization and prediction. Hundreds of seismic attributes have been introduced in the last 30 years. Among the seismic attributes targeting different reservoir features, the autoencoder (AE) receives a significant amount of attention, as it extracts deep attributes of seismic data, providing more details of seismic lateral features than other seismic waveform data and seismic attributes. However, data-driven deep attributes bring new challenges to interpretation as they lack the support of intrinsic physical mechanisms. Hence, a shared AE (S-AE) method is proposed in this article, which can extract seismic deep attributes and fuse traditional seismic attributes simultaneously. An S-AE is a revised version of an AE, which consists of an encoder and decoder. An S-AE takes the seismic waveform as the input of the encoder and obtains the deep attribute, and the decoder then transforms the deep attribute to reconstruct the seismic waveforms and attributes. In an S-AE, the network in front of the decoder is shared, while the networks after the decoder consist of independent layers. Such a network structure ensures the effect of reconstruction and associates seismic attributes with the extracted deep attribute, so as to achieve the purpose of attribute fusion and deep attribute extraction. The proposed S-AE method is compared with conventional seismic data fusion methods, such as RGB and principal component analysis, and the superiority of the S-AE is demonstrated in both synthetic and field applications.

Seismic exploration is a primary tool for imaging complex subsurface structures and is typically classified by acquisition method into surface seismic and well seismic. Surface seismic is well-suited for imaging large-scale structures, while well seismic provides higher resolution of small-scale features near the well. In principle, joint application of both allows for more comprehensive characterization of subsurface structures. However, the absence of a mature workflow for well–surface joint imaging remains a challenge. Here, we present a comprehensive workflow for well–surface joint imaging, integrating seismic interferometry (SI) and data fusion to overcome this limitation. The workflow leverages SI to redatum well data into a virtual surface acquisition geometry. We then apply reverse time migration (RTM) separately to this virtual dataset and to the field-acquired surface data. The resulting images are subsequently merged to form a unified image volume, thereby integrating the high-resolution structural details from well measurements with the broad spatial context of surface seismic. Numerical experiments and a field application demonstrate that integrating surface and well data preserves the strengths of surface seismic for large-scale shallow structures while substantially improving the resolution of deep and small-scale features. This joint imaging approach shows promise for wider application in geologically complex settings.

Seismic images are data collected by sending seismic waves to the earth subsurface, recording the reflection and providing subsurface structural information. Seismic attributes are quantities derived from seismic data and provide complementary information. Enhancing seismic images by fusing them with seismic attributes will improve the subsurface visualization and reduce the processing time. In seismic data interpretation, fusion techniques have been used to enhance the resolution and reduce the noise of a single seismic attribute. In this paper, we investigate the enhancement of 3D seismic images using image fusion techniques and neural networks to combine seismic attributes. The paper evaluates the feasibility of using image fusion models pretrained on specific image fusion tasks. These models achieved the best results on their respective tasks and are tested for seismic image fusion. The experiments showed that image fusion techniques are capable of combining up to three seismic attributes without distortion, future studies can increase the number. This is the first study conducted using pretrained models on other types of images for seismic image fusion and the results are promising.

High‐resolution seismic data are essential for interpreting thin‐layered stratigraphy and subtle structures within hardrock media, as this information can lead to better exploration decisions in the mining sector. Conventional resolution enhancement techniques, such as spectral broadening and supervised deep‐learning techniques, often rely on oversimplified assumptions or require high‐resolution training labels. These limitations restrict their applicability in real seismic data processing, especially for hardrock seismic data, which are typically characterized by high velocities, strong heterogeneity and short reflector continuity due to complex emplacement contacts and geological settings. We propose an unsupervised seismic resolution enhancement framework that integrates physics‐guided and attention‐based mechanisms. The framework is designed to address the progressive loss of high‐frequency information in seismic exploration and the limitations of conventional resolution enhancement methods, which struggle to balance imaging fidelity with geological interpretability. The proposed network incorporates coordinate attention blocks and the lightweight Vision Transformer, enabling more effective capture of spatial dependencies and long‐range significant features in complex geological settings. Specifically, our approach utilizes a physics‐constrained deconvolutional loss function, where the predicted reflectivity is regularized by an adaptive sparsity prior and convolved with a wavelet to synthesize seismic traces that are consistent with the observed data. In addition, a robust Charbonnier penalty ensures stable physical fitting, while anisotropic total variation regularization improves lateral continuity. Following this design, the model achieves end‐to‐end recovery of high‐resolution seismic information without requiring high‐resolution labels, thereby explicitly embedding physical constraints into the learning process. Testing results on synthetic and field datasets from two different regions demonstrate that the proposed method significantly enhances vertical resolution, reflector sharpness and lateral continuity, enabling more precise delineation of subtle stratigraphic features within the target intervals. Compared with spectral enhancement and conventional deep‐learning methods, our approach achieves higher seismic reconstruction fidelity and more interpretable reflectivity, providing an option that combines robustness with interpretability for high‐resolution imaging in complex geological conditions.

Enhancing seismic image resolution while effectively suppressing noise remains a critical challenge in accurately characterizing subsurface geological structures for oil and gas exploration. Traditional methods often fail to balance the recovery of fine details with robustness to noise, particularly in complex geological settings or under high-noise conditions. This study proposes a deep learning-based joint model, U-Net Shifted Window (Swin) Transformer-based dense residual network (U-STDRNet). The model integrates the global modeling capability of the Swin Transformer, the hierarchical feature reuse mechanism of the residual dense network, and an attention-guided strategy to jointly perform seismic image super-resolution and denoising. Built upon the U-Net encoder-decoder architecture, the model embeds Swin Transformer-based convolutional residual blocks. These blocks employ both a feature fusion block with the Swin Transformer and a feature fusion block with a convolutional neural network to effectively capture stratigraphic continuity and enhance detailed features such as fault edges. Residual dense blocks further improve weak signal recovery (e.g., thin-layer interfaces) through dense residual connections. Furthermore, the convolutional block attention module is integrated into skip connections, employing a dual-channel spatial weighting mechanism to suppress noise and emphasize key geological regions. Experimental results and field-data experiments demonstrate that U-STDRNet achieves a higher peak signal-to-noise ratio than the traditional U-Net. In addition, the model successfully restores fault and fold continuity details while exhibiting superior noise suppression compared to existing methods.

… natural images based on deep learning, seismic image processing still faces important challenges. First, as mentioned above, improving seismic image … spectrum of the seismic image …

… To ensure a broader spectrum for high-resolution seismic images and enhance model generalization for different peak frequencies in field datasets, the training data pairs incorporate …

Seismic resolution of towed marine-streamer data is affected by free-surface reflections. They strongly modulate the spectrum reducing energy at the so-called notch frequencies, fn = iv/2z {i = 0,1,…,∞}, in which v is the water velocity and z is the source or receiver depth. As a result there is a very strong loss of useful low-frequency energy and usually a similar loss at higher frequencies. The ghost effect occurs both at the source and at the receiver. At the source, the upgoing part of the source wavefield is reflected off the free surface with inverted polarity before its delayed journey into the Earth. At the receiver, the upgoing part of the receiver wavefield is reflected off the free surface with inverted polarity before it travels down to the receiver again. The over/under acquisition method allows separation of the up- and downgoing wavefields at the source (or receiver) using a vertical pair of sources (or receivers) to determine wave direction. In this article, we present the results of two experiments conducted in the Gulf of Mexico in 2004 and 2006 to investigate the use of over/under sources and receivers.

We developed a case study of seismic resolution enhancement for shale-oil reservoirs in the Q Depression, China, featured by rhythmic bedding. We proposed an innovative method for resolution enhancement, called the full-band extension method. We implemented this method in three consecutive steps: wavelet extraction, filter construction, and data filtering. First, we extracted a constant-phase wavelet from the entire seismic data set. Then, we constructed the full-band extension filter in the frequency domain using the least-squares inversion method. Finally, we applied the band extension filter to the entire seismic data set. We determined that this full-band extension method, with a stretched frequency band from 7–70 to 2–90 Hz, may significantly enhance 3D seismic resolution and distinguish reflection events of rhythmite groups in shale-oil reservoirs.

… First of all, we get a highresolution seismic dataset by using the adaptive bandwidth extension in continuous wavelet transform domain (Chen et al.2015). Then part of the low-…

Jo Firth, Idar Horstad and Menne Schakel present the latest developments in BroadSeis broadband technology. The exceptionally broad bandwidth of more than 6 octaves delivered by BroadSeis variable-depth streamers, in combination with a BroadSource multi-level broadband source and advanced imaging algorithms, not only provides unprecedented information about the subsurface, it also produces stunning images. In particular, the additional high signal-to-noise ratios at low frequencies, down to 2.5 Hz, provide extra ‘texture’ as these provide an envelope to the seismic signal which shapes the larger-scale impedance variations, to deliver clear distinction between stratigraphic packages (see Figure 1). This full bandwidth has been exploited in many areas of the world to reduce exploration risk, improve development plans and maximize return on investment.

… High frequencies enhance the resolution and provide detailed … wideband seismic images: a) broaden the linear bandwidth … end the bandwidth is extended by information from seismic …

Over the last few years, the petroleum giant and its partner have effectively implemented new marine seismic technologies in this part of the world. During the acquisition phase, the industry has observed the introduction of novel broadband acquisition techniques such as dual-sensor cable, multiple towed streamers (over/under), slanted and variable depth streamers, and isometric areal recording. The application of these techniques has resulted in a noteworthy enhancement of the recorded data’s bandwidth. The focus of this paper is on the improvement of seismic bandwidth expansion resulting from advancements in marine broadband acquisition, innovative processing techniques, and inversion methodology. The outcome leads to a noteworthy enhancement in the vertical resolution, which proves to be valuable in the identification of thin stacked pay beds and the creation of a reservoir model that is constrained by seismic data. This paper focuses on the imaging aspect, particularly the complex structures. The utilization of wide and full azimuth (Circular) recording and the resolution of Gas wipeout issues through seabed acquisition with Ocean Bottom Cables (OBC) have been advantageous. By utilizing de-ghosted or far-field signature modeled techniques on the processing side, it is possible to increase the bandwidth for both legacy and modern high-quality data, such as Q-marine. A novel de-convolution technique has been developed, which can enhance signal frequency to a considerable extent while minimizing or eliminating any impact on noise. The article presents various wavelet transform techniques that can effectively enhance the signal-to-noise ratio (S/N). The methods are noteworthy due to their ability to be swiftly executed post-stack while incurring minimal expenses. Further, the inversion techniques, with a focus on stochastic elastic inversion, generates broadband data, enabling the identification of pay sand that falls below the quarter of wavelength criteria. The developed techniques are novel and have been validated using authentic Offshore Malaysia data.

The Daqing field, located in the Songliao Basin in northeastern China, is the largest oil field in China. Most production in the Daqing field comes from seismically thin sand bodies with thicknesses between 1 and 15 m. Thus, it is not usually possible to resolve Daqing reservoirs using only conventional seismic data. We have evaluated the effectiveness of seismic multiattribute analysis of bandwidth extended data in resolving and making inferences about these thin layers. Multiattribute analysis uses statistical methods or neural networks to find relationships between well data and seismic attributes to predict some physical property of the earth. This multiattribute analysis was applied separately to conventional seismic data and seismic data that were spectrally broadened using sparse-layer inversion because this inversion method usually increases the vertical resolution of the seismic. Porosity volumes were generated using target porosity logs and conventional seismic attributes, and isofrequency volumes were obtained by spectral decomposition. The resulting resolution, statistical significance, and accuracy in the determination of layer properties were higher for the predictions made using the spectrally broadened volume.

… In practice, the extension of the frequency bandwidth by padding is imperfect and results in … Kallweitt's time limit of resolution; nevertheless, the time limit of resolution is still reduced by …

When seismic waves propagate through the earth, … Seismic wavelet appears to be stretched out, as it is dominated by low-frequency components. In order to enhance seismic resolution, …

… For decades developments in seismic data acquisition and … Increasing the temporal frequency bandwidth in seismic … , etc. one needs high vertical resolution in seismic data. For a layer …

… seismic resolution to the width and frequency content of the seismic wavelet, and conclude that resolution … We discuss the bandwidth limitations of sparse inversion in a later section and …

… Mexico are typically at or below seismic resolution and embedded in deformed strata with … resolution of the seismic data from the northern central Gulf of Mexico by bandwidth extension…

… Traditional seismic data often lack both high and low … Conventional methods for bandwidth extension include seismic … as noise attenuation and seismic resolution enhancement. The …

Seismic processing and interpretation techniques provide important tools for oil and gas exploration in the Songliao Basin in eastern China, which is dominated by terrestrial facies. In the Songliao Basin, a large number of thin-sand reservoirs are widely distributed and they are the primary targets of potential oil and gas exploration and exploitation. An important part of exploration in the Songliao Basin is to accurately describe the distribution of these thin-sand belts and the sand-body shapes. However, the thickness of these thin-sand reservoirs is generally below the resolution of conventional seismic processing. Most reservoirs are thin interbeds of sand and mudstones with strong vertical and lateral variations. This makes it difficult to accurately predict the vertical and horizontal distribution of the thin-sand bodies using conventional seismic processing and interpretation methods. In addition, these lithologic traps are difficult to identify due to the complex controlling factors and distribution characteristics and the strong concealment. These challenges motivate us to improve the seismic data quality to help delineate thin-sand reservoirs. We have used the broadband, wide-azimuth, and high-density integrated seismic exploration technique to help delineate thin reservoirs. We first use field single-point excitation and single-point receiver acquisition to obtain seismic data with wide frequency bands, wide azimuth angles, and high folds, which contain rich geologic information. Next, we perform near-surface Q compensation, viscoelastic prestack time migration, seismic attributes, and seismic waveform indication inversion on the newly acquired seismic data. The 3D case study indicates the benefits of improving the imaging of thin-sand body and the accuracy of inversion and reservoir characterization using our method.

The high resolving power of seismic measurements has promoted wide adoption of the seismic method in oil and gas and other industries. Studying the evolution of seismic resolution, the different factors affecting it, and the remaining barriers enables an improved understanding of where we are today and what lies ahead. The need to improve seismic resolution is best framed in the context of the interpretation questions being raised and the project stage (e.g., new frontier, appraisal, development, or production). Improvements in resolution do not depend on a single aspect of the seismic workflow but on multiple interconnected components including acquisition, processing, imaging, and interpretation methods and technologies. This paper highlights some of the key milestones in improving seismic resolution. We also conjecture on progress likely to be made in the years ahead and remaining opportunities to enhance seismic resolution.

High-resolution images of subsurface necessitate sophisticated migration methods and high-quality seismic data. Least-Squares Migration (LSM), as an inversion-based method, aims to produce a high-precision subsurface reflectivity model by minimizing the misfit between observed and modelled data. However, the large computational cost for large-scale datasets and convergence issues in case of complex data limit the widespread application of LSM. In this study, we reframe the basic theory of LSM within the perspective of linear system analysis. We identify the point spreading function (PSF) of the underground scattering points is the impulse response of the linear seismic imaging system, with the conventional imaging result can be regarded as the zero-state response of the same system. In this case, the problem of inversion imaging can be expressed as the estimation of the corresponding stimulation function of the imaging system, leveraging the known impulse response and zero-state response. Specifically, we introduce the Gaussian beam propagator to generate PSFs as the impulse response of the inversion imaging system firstly. Then, the Gaussian beam migration (GBM) was employed for the zero-state response of this imaging system. After that, the broadband GBM can be accomplished by a deconvolution with the estimated impulse response and the zero-state response of this system. Where the deconvolution can be expressed by the division in wavenumber domain and implemented by a constrained inversion. Numerical examples demonstrate the effectiveness and potential applications of the proposed broadband imaging method based on the impulse response of the linear imaging system.

This paper discusses how broadband wide-azimuth and high-density seismic has been used to characterize deep-buried hydrocarbon reservoirs as well as fractured carbonate and tight sandstone reservoirs in complex areas. Deeply buried hydrocarbon reservoirs with complex structures can be delineated with improved seismic imaging results due to improved fold, azimuth and offset coverage; fractured carbonate and tight sandstone reservoirs often exhibit strong anisotropy with fractures being the major fluid pathways, and examination of the resultant azimuthal changes in P-wave attributes can provide us with a better definition of their internal structures. In addition, the improved frequency bandwidth of broadband seismic data can provide us with higher seismic resolution than conventional data and better characterization of reservoir heterogeneity, such as lateral variations of sand channels and small slip fault systems. Current practice and various examples have shown that broadband wide-azimuth and high-density three-dimensional (3D) seismic is the undoubted leading-edge tool for exploring the remaining oil in complex reservoirs, and it plays a crucial role in improving reserve growth and hydrocarbon recovery, to meet the ever-increasing energy demand worldwide.

One of the main goals of marine seismic acquisition is to deliver broadband data, rich in both low and high frequencies. The low frequencies are required for deep imaging, for inversion stability and for improved processing such as velocity analyses. The high frequencies are required, in addition to the low-frequencies, for better resolution. The problem of increasing the low-frequency content while maintaining the high-frequency content is caused by the well understood free-surface ghost effect. Towing streamers shallow favors the higher frequencies at the expense of attenuating the low frequencies, while towing streamers deep favors the lower frequencies, at the expense of attenuating frequencies within the seismic bandwidth.

… seismic data processing and interpretation.This study analyzes the spectral characteristics of broadband post-stack seismic … bandwidth adaptively for seismic data in continuous wavelet …

The recent development of techniques to extend the bandwidth of marine towed-streamer surveys has significantly changed the marine seismic landscape. In fact, it has coined the new category of “broadband seismic,” now synonymous with the marine towed-streamer market. The bandwidth challenge for marine towed-streamer seismic is well documented and is related to mitigating, or completely removing, the interference pattern from the interaction of the upgoing primary wave and its surface reflection (i.e., its ghost) at the source and receiver side. The interference results in the ghost notches in the amplitude spectrum which bound the useful bandwidth of the data at the high and low ends of the spectrum.

Summary We develop an efficient method to calculate the broadband seismic illumination and resolution. The point spreading function of seismic image contains the full information for illumination and resolution analyses. Physically, it is the image of a point scatter. Therefore we can obtain the illumination information by calculating the point spreading function. We develop a method to better calculate the point spreading function. The scattered waves from background structure are eliminated, Noise from higher-order inter-scatter multiples are investigated and properly avoided. By converting the point spreading function to the wavenumber domain, methods for illumination and resolution analyses in angle domain are also discussed.

… on the traditional resolution-increasing technology, this paper uses broadband seismic data … of supporting technology processes for broadband seismic data acquisition and processing. …

Abstract The Tibetan plateau is one of the best field laboratories to investigate mechanisms of continental-lithosphere deformation, which contrasts sharply with the typical rigid-plate behavior of the oceanic lithosphere. Several end-member processes have been proposed for the plateau formation involving vertically coherent pure-shear shortening, decoupled upper- and lower-crustal shortening, oblique continental subduction, and crustal channelized flow. In order to test the above models, we conducted an integrated broadband and dense-nodal seismic-array investigation along two traverses across the northern Tibetan plateau margin in the Qilian Shan and its foreland region. The integrated observation provides the first coherent structural image of the lithosphere in general and shallow crust correlative to surface geology in particular in northern Tibet with an updated resolution. Our seismic imaging shows that the surface-exposed south-dipping Qilian Shan frontal thrust zone is closely associated with a low-velocity zone with concentrated seismicity in the upper crust, and along an inclined convertor can be extended downward into the middle-lower crust near a >10-km Moho offset beneath the Haiyuan Fault zone. This dipping feature and an inferred lithospheric detachment zone with oriented anisotropic fabrics constitute a lithospheric-scale thrust zone that bounds crustal-scale thick-skinned thrusts above, coupled with the development of distributed thrust shear zones that cut across the lowermost crust and uppermost mantle. We interpret the bounding lithospheric-scale thrust zone as the basal thrust of a thrust-wedge system across the northern Tibetan plateau margin. A minimum ∼26% bulk shortening strain is accommodated in the thrust-wedge system, which is compatible with the surface-geology constraints. Together with magnetotelluric data, our seismic imaging reveals stark contrasts in the crustal structure and rheology across the left-slip Haiyuan Fault. The involvement of strain partitioning across this regional structure in the thrust wedge supports the earlier proposed transpressional continental underthrusting of North China beneath the Tibetan plateau.

… We can only discuss generalities on the higher vertical resolution of seismic images; to this effect, it would seem that the frequency range should be extended to high frequencies. …

Seismic exploration employing wide-azimuth, broadband, high-density data (i.e. double-width single-height; “double-width” means wide-azimuth and broadband; “single-height” means high-density data, generally referring to small-bin-size data (less than 10 × 10 m); and double-width single-height is an abbreviation) enables more complete wave field information to be recorded, reduces aliasing, and produces abundant low-frequency information, which is conducive to broadband processing and the anisotropic study of seismic data. Based on the acquired double-width single-height seismic data, in this paper, we analyse the wave field characteristics, signal-to-noise ratio and frequency of seismic data. We also design a procedure for processing double-width single-height seismic data. The key techniques in the proposed procedure focus on the high-resolution amplitude-preserved characteristics of double-width single-height seismic data obtained with a low-frequency vibroseis sweep. Faults and sand bodies are characterised and described by using the final imaging results, which embody the advantages of double-width single-height seismic exploration.

… migration moves reflections to their true subsurface positions and yields seismic images of subsurface areas. However, due to limited acquisition aperture, complex overburden structure …

… of high-quality broadband seismic data with improvements in the … seismic imaging technologies have struggled to satisfy the geophysical exploration demand for highresolution imaging, …

… commonly called seismic imaging, which is a very mature technology. In seismic reflection-… (eg, P to Rg) and at best have dip resolution limits imposed by the dominant sensor spacing. …

Ultrahigh-resolution 3D (UHR3D) seismic systems employing a dense array of short streamers represent a significant advancement in the field of marine seismic data acquisition and are an appropriate choice for many near-surface survey applications. Data comparisons between conventional 3D, reprocessed 3D, high-resolution 2D, and UHR3D seismic data illustrate the benefits of a UHR3D acquisition strategy. Results from a recent study of seeps imaged in the Gulf of Mexico (GoM) suggest that UHR3D data can serve as a comprehensive data source for some near-surface geophysical characterizations, satisfying many of the needs often addressed by integrating multiple separate types of survey data.

… acquisition for seismic imaging, and the key problems related to it, to the contribution of wide… density, and broadband seismic data to seismic imaging, and the seismic resolution that can …