基于最大熵谱分解的微裂缝识别技术

Micro-fracture identification technology based on the maximum entropy spectrum decomposition

众所周知,小断层对储层的连通性及油气开发方案的确定具有重要意义,为此引入信息理论中的熵来对储层中的小断层进行预测。首先介绍了最大熵谱分析的原理,其次介绍了最大熵谱分析的Beryman经验公式,最后应用最大熵功率谱方法,对阿曼第五区块Daleel油气田shuaiba储层的高精度三维地震资料进行精细解释,在功率谱分解的振幅数据体上,识别和解释出了以往难以识别的断距在10～15m之间的小断层,为更加清楚地认识油气藏的地质特征、调整注采方案提供了更加可靠的基础资料。

It is well known that small faults are critical to the connectivity of reservoirs and oil/gas development planning.For this reason,the concept of entropy in information theory is introduced to assist the prediction of small faults in reservoirs.First,we introduce the theory of the maximum entropy,and then present the Beryman empirical formula of the maximum entropy,and finally perform fine interpretation of the high-resolution 3D seismic data from the Shuaiba reservoir in the Daleel Field,the Oman's Block 5,by using the maximum entropy spectrum method.Small faults with a displacement within 10-15 m,which were not easy to be identified before,are identified in amplitude data volume after spectrum decomposition.This study provides robust basic data for a good understanding of the geological features and easy adjustment of production-injection program.