Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost

Prediction of TOC Content in Organic-Rich Shale Using Machine Learning Algorithms: Comparative Study of Random Forest, Support Vector Machine, and XGBoost

The total organic carbon (TOC) content of organic-rich shale is a key parameter in screening for potential source rocks and sweet spots of shale oil/gas. Traditional methods of determining the TOC content, such as the geochemical experiments and the empirical mathematical regression method, are eith...

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Bibliographic Details
Main Authors: Jiangtao Sun, Wei Dang, Fengqin Wang, Haikuan Nie, Xiaoliang Wei, Pei Li, Shaohua Zhang, Yubo Feng, Fei Li
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Energies
Subjects:
TOC content
random forest
support vector machine
XGBoost
organic-rich shale
Online Access:https://www.mdpi.com/1996-1073/16/10/4159

Internet

https://www.mdpi.com/1996-1073/16/10/4159

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