Leveraging machine learning for enhanced reservoir permeability estimation in geothermal hotspots: a case study of the Williston Basin

Leveraging machine learning for enhanced reservoir permeability estimation in geothermal hotspots: a case study of the Williston Basin

Abstract Geothermal energy is a large, renewable, and clean source of energy from the earth in the form of heat. Exploring the deeper layers of the Williston Basin has revealed favorable reservoir temperatures, particularly in the western areas where high heat flows are prevalent. The quality of a g...

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Bibliographic Details
Main Authors: Abdul-Muaizz Koray, Emmanuel Gyimah, Mohamed Metwally, Hamid Rahnema, Olusegun Tomomewo
Format: Article
Language:English
Published: SpringerOpen 2025-01-01
Series:Geothermal Energy
Subjects:
Geothermal energy
Reservoir characterization
Machine learning
Neural network
Red River formation
Heat flow
Online Access:https://doi.org/10.1186/s40517-024-00323-4
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https://doi.org/10.1186/s40517-024-00323-4

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