Application of multivariate membership function discrimination method for lithology identification

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,...

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主要な著者: Zhao, Jun, Wang, Feifei, Lu, Yifan
フォーマット: 論文
言語:English
出版事項: Penerbit Universiti Kebangsaan Malaysia 2017
オンライン・アクセス:http://journalarticle.ukm.my/11690/1/24%20SM46%2011.pdf
http://journalarticle.ukm.my/11690/
http://www.ukm.my/jsm/english_journals/vol46num11_2017/contentsVol46num11_2017.htm
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要約: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.