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Joint Interpretation Techniques with Different Azimuth Data to Depict Complex Fault Systems and Reservoir

机译:具有不同方位角数据的联合解释技术描绘复杂故障系统和储层

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The Kongnan area is located in Huanghua depression of Bohai Bay basin in northeast China, where there are complex paleogene fault systems that dissect the area into many different types of reservoirs. It is very difficult to accurately identify the fault systems and to depict the boundaries and interior of the reservoirs with conventional seismic data and seismic interpretation techniques. In order to solve these problems high-density wide azimuth seismic data have been acquired in this area and through processing migration stack data and pre-stack migration gathers from different azimuths have been obtained. Based on these different azimuth seismic data complex fault systems have been accurately identified and reservoir boundaries have been accurately delineated by using a series of techniques including fault system optimal identification technique with different azimuth seismic data joint interpretation, reservoir characterization technique with different azimuth seismic data joint interpretation, special lithologic body recognition technique with different azimuth seismic data joint interpretation, azimuthAVO detection, and azimuth multi-attribute fracture detection. The success rate of drilling has been greatly improved by using these techniques, suggesting the feasibility and effectiveness of our methods.
机译:Kongnan地区位于中国东北地区的黄花坳陷黄花坳陷,其中有复杂的古古代故障系统,将该地区解剖到许多不同类型的水库。非常困难地识别故障系统,并用传统的地震数据和地震解释技术描述储层的边界和内部。为了解决这些问题,在该区域中获取了高密度宽方位地震数据,并且通过处理迁移堆栈数据并获得了来自不同方位角的堆叠迁移收集。基于这些不同的方形地震数据复杂故障系统已经准确识别,并且通过使用具有不同方位震作数据联合解释的故障系统最优识别技术,储层表征技术的一系列技术进行了准确地识别了储层界限,具有不同方位震动数据关节的储层表征技术解释,特殊岩性体识别技术,不同方位震作数据联合解释,AzimuthaVo检测和方位角多属性裂缝检测。通过使用这些技术,钻探的成功率得到了大大改善,这表明我们方法的可行性和有效性。

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