典型文献
Lithology Classification Based on Set-Valued Identification Method
文献摘要：
Lithology classification using well logs plays a key role in reservoir exploration.This paper studies the problem of lithology identification based on the set-valued method(SV),which uses the SV model to establish the relation between logging data and lithologic types at a certain depth point.In particular,the system model is built on the assumption that the noise between logging data and lithologic types is normally distributed,and then the system parameters are estimated by SV method based on the existing identification criteria.The logging data of Shengli Oilfield in Jiyang Depression are used to verify the effectiveness of SV method.The results indicate that the SV model classifies lithology more accurately than the Logistic Regression model(LR)and more stably than uninterpretable models on imbalanced dataset.Specifically,the Macro-F1 of the SV models(i.e.,SV(3),SV(5),and SV(7))are higher than 85％,where the sandstone samples account for only 22％.In addition,the SV(7)lithology identification system achieves the best stability,which is of great practical significance to reservoir exploration.
文献关键词：
中图分类号：
作者姓名：
LI Jing;WU Lifang;Lü Wenjun;WANG Ting;KANG Yu;FENG Deyong;ZHOU Hansheng
作者机构：
Department of Automation,University of Science and Technology of China,Hefei 230027,China;Key Laboratory of Systems and Control,Institute of Systems Science,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China; School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100190,China;Institute of Artificial Intelligence,University of Science and Technology Beijing,Beijing 100083,China;Shengli Geophysical Research Institute,SINOPEC Group,Dongying 257022,China;Institute of Artificial Intelligence,Hefei Comprehensive National Science Center,Hefei 230088,China
文献出处：
引用格式：
[1]LI Jing;WU Lifang;Lü Wenjun;WANG Ting;KANG Yu;FENG Deyong;ZHOU Hansheng-.Lithology Classification Based on Set-Valued Identification Method)[J].系统科学与复杂性学报（英文版）,2022(05):1637-1652
A类：
Shengli,Jiyang,uninterpretable
B类：
Lithology,Classification,Based,Set,Valued,Identification,Method,classification,using,well,logs,plays,key,role,reservoir,exploration,This,paper,studies,problem,lithology,identification,valued,method,SV,which,uses,establish,relation,between,logging,lithologic,types,certain,depth,point,In,particular,system,built,assumption,that,noise,normally,distributed,then,parameters,are,estimated,by,existing,criteria,Oilfield,Depression,used,verify,effectiveness,results,indicate,classifies,more,accurately,than,Regression,LR,stably,models,imbalanced,dataset,Specifically,Macro,higher,where,sandstone,samples,account,only,addition,achieves,best,stability,great,practical,significance
AB值：
0.556084
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