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  2. 地质与地球物理研究所
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  4. 中国科学院油气资源研究重点实验室
Application of Geologically Constrained Machine Learning Method in Characterizing Paleokarst Reservoirs of Tarim Basin, China

文献类型：期刊论文

作者Xin, Wei4; Tian, Fei1,2,3; Shan, Xiaocai1,2,3; Zhou, Yongjian1,2,3; Rong, Huazhong4; Yang, Changchun1,2,3
刊名WATER
出版日期2020-06-01
卷号12期号:6页码:18
关键词karst system machine learning Hilbert-Huang transform waveform cluster seismic interpretation paleo-channels
DOI10.3390/w12061765
英文摘要As deep carbonate fracture-cavity paleokarst reservoirs are deeply buried and highly heterogeneous, and the responded seismic signals have weak amplitudes and low signal-to-noise ratios. Machine learning in seismic exploration provides a new perspective to solve the above problems, which is rapidly developing with compelling results. Applying machine learning algorithms directly on deep seismic signals or seismic attributes of deep carbonate fracture-cavity reservoirs without any prior knowledge constraints will result in wasted computation and reduce the accuracy. We propose a method of combining geological constraints and machine learning to describe deep carbonate fracture-cavity paleokarst reservoirs. By empirical mode decomposition, the time-frequency features of the seismic data are obtained and then a sensitive frequency is selected using geological prior constraints, which is input to fuzzy C-means cluster for characterizing the reservoir distribution. Application on Tahe oilfield data shows the potential of highlighting subtle geologic structures that might otherwise escape unnoticed by applying machine learning directly.
WOS关键词EMPIRICAL MODE DECOMPOSITION ; TAHE OIL-FIELD ; SYSTEM ; ATTRIBUTES ; NETWORK ; UPLIFT ; AREA
资助项目Chinese National Natural Science Foundation[41504142] ; Chinese National Natural Science Foundation[41502149] ; Chinese National Natural Science Foundation[U1663204] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA14050101] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA14040201] ; Chinese National Major Fundamental Research Developing Project[2017ZX05008-004] ; Fundamental Research Funds for the Central Universities of China[ZY1927] ; China Postdoctoral Foundation[2015M570148] ; Horizontal Cooperation Project[H2020009]
WOS研究方向Water Resources
语种英语
WOS记录号WOS:000552492200001
出版者MDPI
资助机构Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Major Fundamental Research Developing Project ; Chinese National Major Fundamental Research Developing Project ; Fundamental Research Funds for the Central Universities of China ; Fundamental Research Funds for the Central Universities of China ; China Postdoctoral Foundation ; China Postdoctoral Foundation ; Horizontal Cooperation Project ; Horizontal Cooperation Project ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Major Fundamental Research Developing Project ; Chinese National Major Fundamental Research Developing Project ; Fundamental Research Funds for the Central Universities of China ; Fundamental Research Funds for the Central Universities of China ; China Postdoctoral Foundation ; China Postdoctoral Foundation ; Horizontal Cooperation Project ; Horizontal Cooperation Project ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Major Fundamental Research Developing Project ; Chinese National Major Fundamental Research Developing Project ; Fundamental Research Funds for the Central Universities of China ; Fundamental Research Funds for the Central Universities of China ; China Postdoctoral Foundation ; China Postdoctoral Foundation ; Horizontal Cooperation Project ; Horizontal Cooperation Project ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Major Fundamental Research Developing Project ; Chinese National Major Fundamental Research Developing Project ; Fundamental Research Funds for the Central Universities of China ; Fundamental Research Funds for the Central Universities of China ; China Postdoctoral Foundation ; China Postdoctoral Foundation ; Horizontal Cooperation Project ; Horizontal Cooperation Project
源URL[http://ir.iggcas.ac.cn/handle/132A11/97584]  
专题地质与地球物理研究所_中国科学院油气资源研究重点实验室
通讯作者Xin, Wei
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Earth Sci, Beijing 100029, Peoples R China
3.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resources Res, Beijing 100029, Peoples R China
4.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 Xin, Wei,Tian, Fei,Shan, Xiaocai,et al. Application of Geologically Constrained Machine Learning Method in Characterizing Paleokarst Reservoirs of Tarim Basin, China[J]. WATER,2020,12(6):18.
APA Xin, Wei,Tian, Fei,Shan, Xiaocai,Zhou, Yongjian,Rong, Huazhong,&Yang, Changchun.(2020).Application of Geologically Constrained Machine Learning Method in Characterizing Paleokarst Reservoirs of Tarim Basin, China.WATER,12(6),18.
MLA Xin, Wei,et al."Application of Geologically Constrained Machine Learning Method in Characterizing Paleokarst Reservoirs of Tarim Basin, China".WATER 12.6(2020):18.

入库方式： OAI收割

来源：地质与地球物理研究所

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