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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
0 Stars
Publicly accessible
1 Resources
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Publicly accessible
Utah FORGE: Well 58-32 Injection Test Data
This submission contains pressure and flow time series data from the reservoir testing of Well 58-32. These activities were part of the Utah FORGE Phase 2B site suitability confirmatory testing.
Podgorney, R. and McLennan, J. Idaho National Laboratory
Dec 07, 2018
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Analysis of downhole data from USU-1 well Leidos Technical Report
USU Camas-1 is a geothermal test well drilled in Camas Prairie, Idaho, in the Summer and Fall of 2018. The purpose of this test well was to validate Play Fairway methodologies of the Snake River Plain Play Fairway Analysis project.
In this report, test data are analyzed to infer...
Garg, S. and Goranson, C. Utah State University
Dec 04, 2018
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Utah FORGE: Discrete Fracture Network (DFN) 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. and Podgorney, R. Golder Associates Inc.
Jun 24, 2020
66 Resources
0 Stars
Publicly accessible
66 Resources
0 Stars
Publicly accessible
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
0 Stars
Curated
3 Resources
0 Stars
Curated
Utah FORGE: Well 58-32 Stimulation Conference Paper and Data
The U.S. Department of Energy's (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in ...
Best, S. Energy and Geoscience Institute at the University of Utah
Apr 24, 2019
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Utah FORGE: Well 58-32 Stimulation Data
Pressure, temperature, and flow data from open-hole, upper perforation, and lower perforation well stimulations gathered from various tools collected at well 58-32 during phase 2C.
Best, S. Geothermal Resource Group
Apr 20, 2019
16 Resources
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible