花岗岩储层裂缝评价及其横向预测  

Fracture Evaluation of Granite Reservoir and Its Lateral Predication

作　　者：罗利[1] 任兴国[1] 姚声贤[1] 

机构地区：[1]四川测井公司

出　　处：《测井技术》1998年第3期204-207,211,共5页Well Logging Technology

摘　　要：罗利，任兴国，姚声贤．花岗岩储层裂缝评价及其横向预测，测井技术，１９９８，２２（３）：２０４～２０７分析了研究区块花岗岩的岩电特征。用密度、中子资料确定其岩石成分；用常规资料准确识别裂缝，识别结果与井周声波成像处理结果吻合；用地层倾角描述裂缝类型和产状；用有限元素法反演研究区块的应力场，将得到的应力场参数与测井处理的裂缝发育度结合，设计神经网络进行网络训练，得到将应力场转换为裂缝发育度的模型；使用模型参数，得出每一单元的裂缝发育度，根据裂缝发育度的大小分布预测出研究区块的裂缝发育带。这种裂缝发育带横向预测技术更合理，预测结果更可信。The electrical property of granite from the interested block is analyzed and its rock composition determined using DEN and CNL data. The results of fracture identification by conventional log data agree with that of CBIL. The type and occurrence of fracture is given by diplog data. Stress field of the survied block is inversed by finite element method. The combination of the parameters for stress field obtained and the extent of fracture development from log analysis is used to set up a model for converting the above stress field into fracture development by training neural network designed. Fracture development per one unit is evaluated using models parameters. Based on the distribution of fracture development,fracture development zones are predicted. This lateral predication technique for fracture development zone is more reasonable and the result is more reliable.

关 键 词：花岗岩 裂缝性储集层 储集层 神经网络 油气藏 

分 类 号：P618.130.2[天文地球—矿床学]