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Machine Learning-Based Fracturability Evaluation of Coalbed Methane Reservoirs: A Fracturing Index Framework That Integrates Rock Mechanical Properties and In Situ Stress.

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Title: Machine Learning-Based Fracturability Evaluation of Coalbed Methane Reservoirs: A Fracturing Index Framework That Integrates Rock Mechanical Properties and In Situ Stress.
Authors: Jian, Hao1,2, Ding, Wenlong1,2, dingwenlong2006@126.com, Liu, Zhong3, Li, Yuntao1,2, Zhang, Pengbao1,2,3, Zhang, Mengyang1,2,3, He, Xiang1,2
Source: Applied Sciences (2076-3417); Apr2026, Vol. 16 Issue 7, p3502, 35p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 192959845
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Machine Learning-Based Fracturability Evaluation of Coalbed Methane Reservoirs: A Fracturing Index Framework That Integrates Rock Mechanical Properties and In Situ Stress.
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      – Type: doi
        Value: 10.3390/app16073502
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      – Code: eng
        Text: English
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        PageCount: 35
        StartPage: 3502
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      – TitleFull: Machine Learning-Based Fracturability Evaluation of Coalbed Methane Reservoirs: A Fracturing Index Framework That Integrates Rock Mechanical Properties and In Situ Stress.
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            NameFull: Jian, Hao
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            NameFull: Zhang, Pengbao
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            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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