Quantifying the potential of the Raniganj Basin for shale gas exploration and CO2 sequestration using a deep learning framework

Quantifying the potential of the Raniganj Basin for shale gas exploration and CO2 sequestration using a deep learning framework

Abstract One key parameter for estimating shale gas potential and evaluating CO2 storage capacity in shale formation is total organic carbon (TOC) content. Traditional TOC estimation methods, such as the ΔlogR technique and shallow artificial neural networks (ANN), often exhibit low correlation with...

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Bibliographic Details
Main Authors: Nasif Ahmed Shaik, Mannat Khanna, Nimisha Vedanti
Format: Article
Language:English
Published: SpringerOpen 2025-03-01
Series:Journal of Petroleum Exploration and Production Technology
Subjects:
Deep learning model
Total organic carbon
Shale gas
CO2 sequestration
Barren Measures shale
Raniganj Basin
Online Access:https://doi.org/10.1007/s13202-025-01978-w
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