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Rare Earth Element Concentrations in Submarine Hydrothermal Fluids
Rare earth element concentrations in submarine hydrothermal fluids from Alarcon Rise, East Pacific Rise, REE concentrations in submarine hydrothermal fluids from Pescadero Basin, Gulf of California, and the Cleft vent field, southern Juan de Fuca Ridge. Data are not corrected to z...
Fowler, A. and Zierenberg, R. University of California
Oct 27, 2017
3 Resources
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3 Resources
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Google Earth Locations of USA and Seafloor Hydrothermal Vents with Associated Rare Earth Element Data
Google Earth .kmz files that contain the locations of geothermal wells and thermal springs in the USA, and seafloor hydrothermal vents that have associated rare earth element data. The file does not contain the actual data, the actual data is available through the GDR website in t...
Fowler, A. University of California
Feb 10, 2016
2 Resources
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2 Resources
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Validation of Innovative Exploration Technologies for Newberry Volcano: Drill Site Location Map
Newberry seeks to explore "blind" (no surface evidence) convective hydrothermal systems associated with a young silicic pluton on the flanks of Newberry Volcano. This project will employ a combination of innovative and conventional techniques to identify the location of subsurface...
Jaffe, T. Davenport Newberry Holdings, LLC
Jan 01, 2012
1 Resources
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1 Resources
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Geothermal Water Use: Life Cycle Water Consumption, Water Resource Assessment, and Water Policy Framework
This report examines life cycle water consumption for various geothermal technologies to better understand factors that affect water consumption across the life cycle (e.g., power plant cooling, belowground fluid losses) and to assess the potential water challenges that future geo...
Schroeder, J. et al Argonne National Laboratory
Jun 10, 2014
8 Resources
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8 Resources
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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
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