新场深层致密碎屑岩储层裂缝常规测井识别

Conventional log identification of fractures in the deep tight clastic reservoir in Xinchang area

(1.斯伦贝谢中国公司，北京100015；2.成都理工大学“油气藏地质与开发工程国家重点实验室”,四川成都610059；3.中国石油化工股份有限公司西北油田分公司，新疆乌鲁木齐830011)

Wang Xiao,Schlumberger China,Beijing 100015,China

在新场深层致密碎屑岩储层中,裂缝既是油气储集空间,又是重要的油气运移通道,裂缝的发育对改善储层品质起着重要作用。因此,裂缝识别是该地区储层评价的重要研究内容。以往利用单一的测井方法识别裂缝存在一定的局限性,有必要综合多种方法进行裂缝识别研究。首先,通过岩心观察从宏观层面上把握研究区裂缝的发育情况，用交会图法分析裂缝的常规测井响应特征；然后,通过判别分析优选出裂缝测井响应参数，建立起两类裂缝的判别方程,采用概率神经网络法对单井进行两类裂缝识别。最后，综合应用上述方法对单井进行裂缝识别，与岩心资料对比结果表明该套方法的裂缝识别效果较好。

In the deep tight clastic reservoir of Xinchang area,the fractures are the storage space and significant migration pathway for hydrocarbon,which plays an important role for improving the quality of reservoirs.Therefore,fracture identification is an important part for the reservoir evaluation in the area.The conventional fracture identification has some limitation by using single logging technique;we need to integrate many methods to study the fractures.Firstly,the development of fractures was verified by core observation from macro level,and its conventional logging response was analyzed by crossploting.Then,discrimination analysis was adopted to optimize fracture logging response parameters and established discrimination equation of the two kinds of fractures,and probability neural network (PNN) method was utilized to identify the two kinds of fractures.Finally,the above methods were integrated to carry out fracture identification on single well.Compared with core data,the methods are better for fracture identification.

10.3969/j.issn.1000-1441.2011.06.016