Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs

doi:10.1155/2021/9321565

CORC > 深海科学与工程研究所 > 中国科学院深海科学与工程研究所 > 深海科学研究部 > 深海地球物理与资源研究室

	Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs
	Yu, Jie 1,2; Zhu, Linqi 3; Qin, Ruibao 2; Zhang, Zhansong 1; Li Li 2; Huang, Tao 2
刊名	GEOFLUIDS
	2021-08-21
卷号	2021 页码:8
ISSN号	1468-8115
DOI	10.1155/2021/9321565
英文摘要	The accurate calculation of the gas content of coalbed bed methane (CBM) reservoirs is of great significance. However, due to the weak correlation between the logging response of coalbed methane reservoirs and the gas content parameters and strong nonlinear characteristics, it is difficult for conventional gas content calculation algorithms to obtain more reliable results. This paper proposes a CBM reservoir gas content assessment method combining K-means clustering and random forest. The K-means clustering is used to divide the reservoirs and distinguish the types to establish a random forest model. Judging from the evaluation effect of the research block, the prediction accuracy of the new method is significantly higher than that of the original method, and more accurate gas content prediction values can be obtained for different types of reservoirs. Studies have shown that this method can help the gas content evaluation of CBM reservoirs, improve the accuracy of gas content evaluation, and better support the exploration and development of CBM reservoirs. The results of this study show that the random forest method based on clustering can effectively distinguish the relationship between different logging responses and gas content. On this basis, the random forest algorithm modeling can effectively characterize the complex relationship between gas content and logging curve response. In the case of poor correlation between gas content and logging curve, the gas content of the reservoir can also be accurately calculated.
资助项目	CNOOC information construction major project[2019-KJZC-010] ; Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology[2MGQNLM-KF202004] ; China Postdoctoral Science Foundation[2021M690161] ; China Postdoctoral Science Foundation[2021T140691] ; Post-doctorate Funded Project in Hainan Province ; Chinese Academy of Sciences-Special Research Assistant Projec ; China Engineering Technology Development Strategy Hainan Research Institute Consulting Research Project[20-HN-ZT-01] ; Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education[K2021-03] ; Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education[K2021-08]
WOS关键词	COALFIELD ; SEAMS
WOS研究方向	Geochemistry & Geophysics ; Geology
语种	英语
出版者	WILEY-HINDAWI
WOS记录号	WOS:000691133400003
资助机构	CNOOC information construction major project ; Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology ; China Postdoctoral Science Foundation ; Post-doctorate Funded Project in Hainan Province ; Chinese Academy of Sciences-Special Research Assistant Projec ; China Engineering Technology Development Strategy Hainan Research Institute Consulting Research Project ; Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education
内容类型	期刊论文
源URL	[http://ir.idsse.ac.cn/handle/183446/8883]
专题	深海科学研究部_深海地球物理与资源研究室
通讯作者	Zhu, Linqi
作者单位	1.Yangtze Univ, Wuhan 430100, Peoples R China 2.CNOOC Res Inst, Beijing 100027, Peoples R China 3.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Peoples R China
推荐引用方式 GB/T 7714	Yu, Jie,Zhu, Linqi,Qin, Ruibao,et al. Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs[J]. GEOFLUIDS,2021,2021:8.
APA	Yu, Jie,Zhu, Linqi,Qin, Ruibao,Zhang, Zhansong,Li Li,&Huang, Tao.(2021).Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs.GEOFLUIDS,2021,8.
MLA	Yu, Jie,et al."Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs".GEOFLUIDS 2021(2021):8.