3D seismic prediction of low rank coalbed methane enrichment area in the southern margin of Junggar Basin
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摘要: 为深化煤层气资源潜力调查与评价，开展了准噶尔盆地南缘呼图壁区块三维地震勘探。地震数据采集针对宽方位、小道距和高覆盖次数目标设计，采用16L×6S×160R观测系统。地震数据处理针对复杂地貌野外静校正问题和陡倾角煤层成像精度要求高的技术难点，建立了高分辨率三维地震数据处理流程，以满足煤层气富集区预测需求。根据影响煤层气富集的主要地质因素(煤层埋深、断层特征、煤层厚度、煤层顶板岩性和煤层含气量等)定义了煤层气富集区划分原则和有利区分类模式。基于三维地震资料，将地震资料解释与地震属性分析相结合，利用地震岩性反演结果获得煤层厚度、煤层顶板岩性和煤层含气量信息。在钻孔约束下，进行了研究区B4煤层气富集区预测，提出了煤层气开发生产井部署建议。Abstract: In order to investigate and evaluate the potential of CBM Resources in the southern margin of the Junggar Basin, this study conducted 3D seismic exploration in the Hutubi block. The seismic acquisition design tailors to wide azimuth, small receiver distance and high folds, the seismic geometry design includes 16 lines, 6 shots and 160 receivers. Given the serious static problems in mountainous terrain and imaging accuracy of steep dip coal seam in the seismic data processing, a high-resolution 3D seismic data processing flow is therefore established to meet the prediction requirement of coalbed methane enrichment area. The dividing principle of the coalbed methane enrichment area and the classification model of favorable area are proposed in line with the main seismic geological factors affecting coalbed methane enrichment, such as the coal seam depth, the faults characteristics, the coal seam thickness, the coal seam roof lithology and the coal seam gas content. Based on 3D seismic data, this study combined seismic data interpretation and seismic attribute analysis to obtain data on coal seam thickness, coal seam roof lithology, and coal seam gas content by using seismic lithology inversion results. Under the constraints of logging, this study made predictions of the B4 coalbed methane enrichment area in the research area, and put forward suggestions for deploying coal bed gas production borehole.
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图 5 B4煤层沿层最大波峰振幅属性与断层叠合图
Figure 5. Maximum wave peak amplitude horizon attribute and fault overlapping graph of B4 coal seam
图 7 基于叠后波阻抗反演预测煤层厚度
Figure 7. Prediction of coal seam thickness based on post stack impedance inversion
图 8 基于自然伽马拟声波反演的B4煤层顶板岩性分布
Figure 8. Roof lithology distribution of B4 coal seam based on natural gamma pseudo acoustic inversion
图 9 基于叠前AVO反演的B4煤层含气量预测
Figure 9. Gas content prediction of B4 coal seam based on pre-stack AVO inversion
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