镇泾地区长8油层组裂缝特征及裂缝识别方法

Chang 8 oil formation fracture feature and identification method in Zhenjing area

镇泾区块长8油层组属于典型的低孔、低渗储层,裂缝是储层的主要运移通道,因此油气聚集和油藏开发效果与裂缝有重要关系,裂缝的识别对油气生产有很大的意义。在野外和岩心裂缝观察特征分析的基础之上,综合常规测井资料和取心资料构建了砂、泥岩样本共65个,利用常规测井裂缝识别模式对储层裂缝进行识别,可将有效缝识别出来。引入概率神经网络(PNN)方法对优选出的35个样本进行训练,建立裂缝识别模型。利用该模型对10个预测样本进行识别,正确识别9个,预测精度达90%,对27个建模样本进行回判,准确率达100%。通过岩心资料对比发现,当目标受到多因素影响且非线性关系比较强时,采用PNN进行判别具有精度高、效率高的优势。

Zhenjing block Chang 8 oil layer is typical low porous,low permeable reservoir,fracture is main migration path,therefore the oil gas accumulation and reservoir development effect has important relations with fracture,the identification of fracture has very significant meaning to the oil and gas production.In this article,based on field and core fracture observation analysis,combined conventional log data and coring data,65 sand and mud rock sample have been built up.Using conventional log fracture identification mode to identify the reservoir fracture,which can identify effective fracture.Introducing probabilistic neutral network to optimal 35 samples,build up fracture identification fracture.Using this model to identify 19 samples,9 can be identified correctly,the forecast precision reach to 90%.The returning discriminant ratio is 100% on 27 model samples.According to coring data comparison,when the goal is under the multi-factor influence,and the nonlinear relation is rather strong,applying PNN to identify has advantage of high precision and efficiency.