Application of Multivariate Membership Function Discrimination Method for Lithology Identification

被引:2
|
作者
Zhao, Jun [1 ]
Wang, Feifei [1 ]
Lu, Yifan [1 ]
机构
[1] Southwest Petr Univ, Chengdu 610500, Sichuan, Peoples R China
来源
SAINS MALAYSIANA | 2017年 / 46卷 / 11期
关键词
Fuzzy theory; lithology identification; logging interpretation; multivariate membership function;
D O I
10.17576/jsm-2017-4611-24
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Formation lithology identification is an indispensable link in oil and gas exploration. Precision of the traditional recognition method is difficult to guarantee when trying to identify lithology of particular formation with strong heterogeneity and complex structure. In order to remove this defect, multivariate membership function discrimination method is proposed, which regard to lithology identification as a linear model in the fuzzy domain and obtain aimed result with the multivariate membership function established. It is indicated by the test on lower carboniferous Bachu group bioclastic limestone section and Donghe sandstone section reservoir on T Field H area that satisfactory accuracy can be achieved in both clastic rock and carbonate formation and obvious advantages are unfold when dealing with complex formations, which shows a good application prospect and provides a new thought to solve complex problems on oilfield exploration and development with fuzzy theory.
引用
收藏
页码:2223 / 2229
页数:7
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