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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
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1 Resources
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
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6 Resources
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Utah FORGE: 2023 Large Upscaled Discrete Fracture Network Models
This dataset includes the data and a report on the large upscaled discrete fracture network modeling done for the Utah FORGE project in 2023. The FORGE modeling team is making five discrete fracture network (DFN) realizations of a large reservoir model available to researchers. Th...
Finnila, A. Energy and Geoscience Institute at the University of Utah
Oct 02, 2023
17 Resources
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17 Resources
0 Stars
Publicly accessible