主成分分析法在碳酸盐岩岩性识别中的应用——以地区寒武系碳酸盐岩储层为例  

Application of principal component analysis in carbonate lithology identification:a case study of the Cambrian carbonate reservoir in YH field

作　　者：刘爱疆[1,2] 左烈[3] 李景景[4] 李瑞[1,2] 张玮[2] 

机构地区：[1]成都理工大学油气藏地质及开发工程国家重点实验室,四川成都610059 [2]成都理工大学地球物理学院,四川成都610059 [3]中国石油新疆油田分公司陆梁油田作业区,新疆克拉玛依834000 [4]中国石油新疆油田分公司勘探开发研究院,新疆克拉玛依834000

出　　处：《石油与天然气地质》2013年第2期192-196,共5页Oil & Gas Geology

摘　　要：在复杂岩性油气藏储层评价中,利用测井曲线直接判别复杂岩性一直存在着多解性和不确定性。利用测井曲线构建主成分变量,选取累积方差贡献率大于85%的主成分代表输入的多维测井信息,保证在原始信息损失最小的情况下,以少量综合变量取代原有多维测井信息,简化数据结构,从而解决复杂的碳酸盐岩岩性识别的难题。文中根据YH地区寒武系碳酸盐岩储层实测的自然伽马测井(GR)值、中子孔隙度测井(CNL)值、密度测井(DEN)值、声波时差测井(AC)值和深侧向电阻率值(RT),构建F1—F5五个综合变量,其中F1和F2两个主变量占总贡献率的87.73%,可以有效地代替原始的多维测井信息。实例表明,通过岩心薄片分析定名的岩性数据,根据F1和F2主成分的交会图分析,可以有效地识别碳酸盐岩的岩性。该方法在YH地区寒武系碳酸盐岩储层岩性识别中取得了良好的应用效果。Log-based direct identification of complex lithology is still challenging in complex reservoir evaluation due to the ambiguity and uncertainty of results.The principal component variables constructed based on logging curves and having an accumulative variance contribution ratio more than 85% were selected to represent the inputs of multidimensional variables.This method can simplify the data structure and solve the problem of carbonate lithology identification through replacing the original multidimensional variables with a small amount of comprehensive variables while keeping the original information as much as possible.Five comprehensive variables including F1-F5 are constructed by using the measured GR,CNL,DEN,AC and RT of the Cambrian carbonate reservoirs in YH field.Among these variables,the F1 and F2 principle variables account for 87.73% of the total contribution ratio,so they can replace the multidimensional variables efficiently.The case study shows that the lithology of carbonates can be effectively identified through analysis on crossplot of of F1 and F2.This method has been successfully applied to identify the lithology of the Cambrian carbonates in YH field.

关 键 词：测井曲线 主成分分析 岩性识别 碳酸盐岩 寒武系 

分 类 号：TE121.1[石油与天然气工程—油气勘探]