潜山油藏多因素神经网络裂缝综合识别技术——以垦利潜山油藏为例  

Integrated identification technology of multiple -factor neural network for buried hill reservoir

作　　者：陶国秀[1] 

机构地区：[1]中国石油大学(北京)地球资源与信息学院

出　　处：《油气地质与采收率》2006年第4期36-38,共3页Petroleum Geology and Recovery Efficiency

摘　　要：针对潜山油藏井间储层预测的难题,利用地震探测技术对潜山油藏裂缝进行预测。运用神经网络和模糊逻辑技术综合多种与裂缝有关的地质因素,对垦利潜山油藏储层中的裂缝进行了定量化预测和描述。预测结果表明,裂缝发育方向主要为北西向,其次为北东及近东西向;通过综合评价将裂缝发育强度细分为3个等级,该技术预测结果与地质认识对应性好,取得了较为理想的效果。The fractures in buried hill reservoir are predicted using seismic detection technology so as to solve the difficulty of crosshole reservoir prediction of the buried hill reservoir. Fractures in Kenli buried hill reservoir are predicted and described quantitatively by using neural network and fuzzy logic techniques combined with many geological factors related to the fractures. Using this new technique,fractures are predicted to be developed in NW direction mainly and in NE and nearly EW direction next. Fractures development intension is divided into three levels after comprehensive evaluation. Prediction results are well corresponding with geological recognitions and the ideal results are achieved.

关 键 词：潜山油藏 裂缝预测 多因素神经网络 综合识别 控制因素 地震属性 

分 类 号：TE344[石油与天然气工程—油气田开发工程]