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A gradient boosting decision tree algorithm combining synthetic minority oversampling technique for lithology identification

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成果类型:
期刊论文
作者:
Zhou, Kaibo;Zhang, Jianyu;Ren, Yusong;Huang, Zhen;Zhao, Luanxiao*
通讯作者:
Zhao, Luanxiao
作者机构:
[Ren, Yusong; Zhou, Kaibo; Zhang, Jianyu] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Key Lab Image Informat Proc & Intelligent Control, Educ Minist China, Wuhan 430074, Peoples R China.
[Huang, Zhen] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430023, Peoples R China.
[Zhao, Luanxiao] Tongji Univ, Sch Ocean & Earth Sci, State Key Lab Marine Geol, Shanghai 200092, Peoples R China.
通讯机构:
[Zhao, Luanxiao] T
Tongji Univ, Sch Ocean & Earth Sci, State Key Lab Marine Geol, Shanghai 200092, Peoples R China.
语种:
英文
关键词:
lithology;reservoir characterization;rock physics
期刊:
GEOPHYSICS
ISSN:
0016-8033
年:
2020
卷:
85
期:
4
页码:
WA147-WA158
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61873101, 41874124]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [2019kfyXJJS137]; Changzhou Key Laboratory of high technology [CM20183004]; Young Elite Scientists Sponsorship Program by CAST [2017QNRC001]
机构署名:
本校为其他机构
院系归属:
电气与电子工程学院
摘要:
Lithology identification based on conventional well-logging data is of great importance for geologic features characterization and reservoir quality evaluation in the exploration and production development of petroleum reservoirs. However, there are some limitations in the traditional lithology identification process: (1) It is very time consuming to build a model so that it cannot realize real-time lithology identification during well drilling, (2) it must be modeled by experienced geologists, which consumes a lot of manpower and material reso...

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