扩展弹性阻抗的使用局限性及渗透率曲线计算

常规拖缆三维地震难以满足西非深水A区块复杂目标、隐蔽油气藏评价的需求, 海底节点(OBN)地震勘探已经成为精细勘探开发的主要技术手段。对比分析了研究区OBN地震与拖缆地震的采集和处理参数, 明确了OBN地震资料具有更高的信噪比、更宽的频带、更好的保幅性。对目的层段开展了5个分角度叠加资料的井震标定, 相关系数达0.84~0.91, 为开展叠前地震反演提供了良好的基础资料。针对研究区小于10 m的薄储层预测难题, 开展了扩展弹性阻抗(EEI)反演, 以孔隙度曲线作为储层预测的目标曲线进行EEI计算, 获得不同角度对应的EEI曲线, 并与孔隙度曲线进行相关性分析, 发现当旋转角度 χ 为29°时, EEI曲线与孔隙度曲线具有最大的负相关性, 为最优角度。建立了EEI(29°)与孔隙度的线性关系, 通过岩石物理正演以及测井解释储层孔隙度门槛值, 定量计算出目的层反演砂岩储层EEI门槛值为5 000 g·cm -3 ·m·s -1 。对比分析了基于不同地震数据的EEI反演结果, 认为基于OBN地震数据的EEI反演在储层预测方面效果更好, 适用性更强。

… , the pre-stack Extended Elastic Impedance (EEI) inversion is used to predict the oil-bearing … -simulation inversion for logging parameters to predict porosity and permeability. According …

This work intends to showcase a validation of the applicability of Extended Elastic Impedance (EEI) inversion method in reservoir characterization and modeling. In order to achieve that, deterministic seismic inversion and extended elastic impedance (EEI) analysis were applied to obtain quantitative estimates of reservoir properties over the Pu field of the West African Congo basin. Optimum EEI angles corresponding to the reservoir properties were then analyzed using well logs data, together with a lithology indicator.  Pre-stack seismic data were simultaneously inverted into density, acoustic and gradient impedances cubes, through model based inversion algorithm. The last two broadband inverted volumes were then projected to corresponding Chi angles proportionate to petrophysical indicators, thus resulting to two broadband EEI volumes. At well locations, the EEI versus petrophysical parameters linear trends were then applied to convert EEI volumes into  porosity and shale volumes based on specified lithology. In order to generate reservoir facies distribution, minimum angle was applied based on background EEI, thus allowing for mapping of reservoir facies. In order to validate the EEI approach, a Geo-statistical model was further developed for the same field. Hence, from  porosity, shale content and background EEI cubes, a comparison was made between the properties generated from the EEI and that generated based on geo-statistical method, which shows that EEI is a robust way of reservoir characterization that  pinpointing favorable reservoir potentials which shall guide future drilling locations.

We use an extended elastic impedance ( EEI ) inversion for quantitative reservoir characterization. The EEI approach is applied to both on-shore and off-shore seismic data where target reservoirs are gas-bearing sands located in sand-shale sequences. The work fl ow we adopt can be divided into three phases. The starting point is a petrophysical analysis in which the relationships between petrophysical and elastic properties are analyzed. The second step of EEI analysis uses a cross-correlation procedure to determine the best chi ( χ ) projection angles for the petrophysical parameters of interest ( i.e. porosity, water saturation and shaliness ) . In the fi nal step, pre-stack seismic data are simultaneously inverted into P -wave velocity, acoustic, and gradient impedances, and the last two elastic volumes are fi nally projected to χ angles corresponding to the target petrophysical parameters. The estimated porosity, water saturation, and shaliness values reveal a proper match at blind well locations. This work shows that EEI is an effective tool for lithology and fl uid prediction in clastic reservoirs. The output of this work can be bene fi cial for static reservoir model building and volumetric calculation and can be also used to determine new potential drilling locations.

… Figure 1 EEI inversion workflow … The porosity of the main production zone is between 22-28%, permeability is between 300-3000mD. Two main production layers are O72 and O73 with …