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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
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6 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
0 Stars
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Hawaii Play Fairway: Preliminary Core Box Photos, Lanai Island, Hawaii
Photos of core samples from Lanai Island. During the third phase of the Hawaii Play Fairway project, further exploration involved drilling a groundwater well in Lanai's Palawai Basin and performing more geophysical surveys. The project deepened an existing water well on Lanai. Dri...
Lautze, N. et al University of Hawaii
Jul 01, 2019
3 Resources
0 Stars
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3 Resources
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Steptoe Valley NV Data Compilation: Understanding a Stratigraphic Hydrothermal Resource through Geophysical Imaging
Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. Provided here are a compilation of newly acqu...
Schwering, P. et al Sandia National Laboratories
Nov 01, 2023
8 Resources
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8 Resources
0 Stars
Publicly accessible
DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period
This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady geothermal field during PoroTomo deployment (2016-Mar-14 to 2016-Mar-26). There is one file correspondin...
Reinisch, E. et al University of Wisconsin
Jun 27, 2018
20 Resources
0 Stars
Curated
20 Resources
0 Stars
Curated
DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested...
Taverna, N. et al National Renewable Energy Laboratory
Jan 24, 2024
14 Resources
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14 Resources
0 Stars
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DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
27 Resources
0 Stars
Publicly accessible
27 Resources
0 Stars
Publicly accessible