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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
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
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
Utah FORGE: Seismic and Other Shapefiles from the Roosevelt Hot Springs Area
Three shapefiles in this submission show the position of proposed seismic line surveys. The mid-crustal velocity anomaly file shows the extent of an anomalously low P-wave velocity zone in the subsurface. Two other files show the extent of known hydrothermal systems in the Rooseve...
Moore, J. Energy and Geoscience Institute at the University of Utah
Mar 22, 2016
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Seismic Survey 2016 Data at San Emidio Nevada
Included here are seismic data recorded at the San Emidio Geothermal field in Nevada. This passive seismic data were collected as part of the DOE-funded Subsurface Technology and Engineering R&D (SubTER) project to advance imaging and characterization of geothermal permeability. ...
Lord, N. et al University of Wisconsin Madison
Jan 05, 2016
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
PoroTomo: Horizontal Distributed Acoustic Sensing (DAS) Measurements During an M 2.3 Explosion
Included here are Distributed Acoustic Sensing (DAS) data collected by the horizontal DAS array at Brady's Hot Springs Geothermal Field. The system recorded this data during an M 2.3 explosion at the Nevada Test Site (NTS), which is located approximately 400km southeast of the fie...
Kratt, C. et al Center for Transformative Environmental Monitoring Programs (CTEMPs)
Dec 18, 2018
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated