基于地震属性技术的储层预测研究——以胜利油田单56区块为例  

Reservoir Prediction Based on Technology of Seismic Attributes——By Taking Wellblock Shan 56 of Shengli Oilfield for Example

作　　者：汪勇[1] 阳和华[1] 桂志先[1] 

机构地区：[1]油气资源与勘探技术教育部重点实验室(长江大学),湖北荆州434023

出　　处：《石油天然气学报》2012年第7期68-71,6,共4页Journal of Oil and Gas Technology

基　　金：国家"十一五"科技重大专项(2008ZX050000230401)

摘　　要：目前地震属性分析技术已成为油气勘探和开发工作中必不可少的常规方法,但地震属性的种类不断增多,对储层预测精度的要求也越来越高,这使得地震属性的提取、优化及应用成为了关键。以胜利油田单56区块馆陶组下段砂体储层为目标,首先在岩石物理统计及属性敏感性分析的基础上提取合适的地震属性,然后采用K-L变换对多种地震属性进行降维处理,最后基于人工神经网络的识别技术对目标层的含油饱和度等储层参数进行了预测,预测的效果较好,为该工区的剩余油开发提供了依据。At present,seismic attribute analysis technology has become an indispensable method in oil and gas exploration and development.Because of the growing variety of seismic attributes and the increasingly high demands for reservoir prediction accuracy,the seismic attribute extraction,optimization and application became the key factors.First by taking the sandbody reservoir in Guantao Formation of Wellblock Shan 56 in Shengli Oilfield as an object of study,the suitable attributes were attracted on the basis of the rock physical statistics and attributes sensitivity analysis,and then the K-L transform was used for the dimension reduction of multiple seismic attributes.Finally the target zone oil saturation parameters are predicted based on artificial neural network identification technology.The effect of prediction is good,and it provides a basis for remaining oil development in the operation area.

关 键 词：地震属性 K-L变换 神经网络 储层预测 

分 类 号：P631.44[天文地球—地质矿产勘探]