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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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EGS Collab: Modeling and Simulation Working Group Teleconference Series (1-98)

This submission contains the presentation slides and recordings from the first 98 EGS Collab Modeling and Simulation Working Group teleconferences. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and resul...

White, M. et al Pacific Northwest National Laboratory

Feb 04, 2020
100 Resources
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Wister, CA Downhole and Seismic Data

This submission contains Downhole geophysical logs associated with Wister, CA Wells 12-27 and 85-20. The logs include Spontaneous Potential (SP), HILT Caliper (HCAL), Gamma Ray (GR), Array Induction (AIT), and Neutron Porosity (NPOR) data. Also included are a well log, Injection T...

Akerley, J. Ormat Nevada Inc

Dec 18, 2010
16 Resources
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Utah FORGE: Well 16A(78)-32 Simplified Discrete Fracture Network Data

The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...

Finnila, A. Golder Associates Inc.

Jun 01, 2021
3 Resources
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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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Utah FORGE: Discrete Fracture Network (DFN) Data

Finnila, A. and Podgorney, R. Golder Associates Inc.

Jun 24, 2020
66 Resources
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