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Machine learning supervised algorithms for gas hydrate identification and saturation estimation in marine reservoirs using well log data:A case study of NGHP-01-19B

Yi-fan Wu Zheng Su Takeshi Tsuji Dai-dai Wu Guang-rong Jin Chao Yang Chuang-ji Feng Neng-you Wu

China Geology2026，Vol.9Issue(3)：P.519-534,I0023-I0027,21.

China Geology2026，Vol.9Issue(3)：P.519-534,I0023-I0027,21.DOI:10.31035/cg2025078

Machine learning supervised algorithms for gas hydrate identification and saturation estimation in marine reservoirs using well log data:A case study of NGHP-01-19B

Yi-fan Wu ¹Zheng Su ¹Takeshi Tsuji ²Dai-dai Wu ¹Guang-rong Jin ¹Chao Yang ¹Chuang-ji Feng ¹Neng-you Wu³

作者信息

1. School of Energy Science and Engineering,University of Science and Technology of China,Guangzhou 510640,China Guangzhou Institute of Energy Conversion,Chinese Academy of Sciences,Guangzhou 510640,China
2. Department of Systems Innovation,School of Engineering,The University of Tokyo,Tokyo 113-8656,Japan
3. Key Laboratory of Gas Hydrate,Ministry of Natural Resources,Qingdao Institute of Marine Geology,China Geological Survey,Qingdao 266237,China Laoshan Laboratory,Qingdao 266200,China
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摘要

关键词

Gas hydrate/Machine learning algorithm/Classification/Regression/Well log data/Archie’s law/Marine geohazards/Global carbon cycle

分类

天文与地球科学

引用本文复制引用

Yi-fan Wu,Zheng Su,Takeshi Tsuji,Dai-dai Wu,Guang-rong Jin,Chao Yang,Chuang-ji Feng,Neng-you Wu..Machine learning supervised algorithms for gas hydrate identification and saturation estimation in marine reservoirs using well log data:A case study of NGHP-01-19B[J].China Geology,2026,9(3):P.519-534,I0023-I0027,21.

基金项目

supported by the China Scholarship Council under the State Scholarship Fund(202506340082) （202506340082）

the Key Project of Guangdong Provincial Key R&D Program(2023B1111050014) （2023B1111050014）

the Youth Promotion Project of the Natural Science Foundation of Guangdong Province(2023A1515030280) （2023A1515030280）

the Guangdong Basic and Applied Basic Research Foundation(2023A1515010926) （2023A1515010926）

the Guangzhou Science and Technology Plan Project(2024A04J9876) （2024A04J9876）

funded by China National Petroleum Corporation(CNPC,2024DQ02-0107)。（CNPC,2024DQ02-0107）

China Geology

ISSN：2096-5192

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