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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
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Utah FORGE 3-2417: Pulsed Interference Tests at Wells 16A(78)-32 and 16B(78)-32 September 2024
This archive contains data and a report from Pulse Interference Tests (PITs), which were conducted on September 4, 2024, immediately following a 30-day recirculation test at the Utah FORGE site. Injection and backflow were induced in well 16A(78)-32 while pressures were measured i...
W Becker, M. et al Rice University
Mar 18, 2025
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
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
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible
Utah FORGE: Groundwater Data
This submission includes two modeled drawdown scenarios with new supply well locations, a total dissolved solids (TDS) concentration grid (raster dataset representing the spatial distribution of TDS), and an excel spreadsheet containing well data.
Moore, J. Energy and Geoscience Institute at the University of Utah
Jul 20, 2016
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible