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Maps, Models and Data from Southeastern Great Basin PFA

This submission includes composite risk segment models in raster format for permeability, heat of the earth, and MT, as well as the final PFA model of geothermal exploration risk in Southwestern Utah, USA. Additionally, this submission has data regarding hydrothermally altered are...

Nash, G. Energy and Geoscience Institute at the University of Utah

Jun 30, 2017
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Utah FORGE: Mineral Mountains West Fault System Report

This archive contains a report on the Mineral Mountains West fault system as part of phase 2C and the evidence for the northern terminus of this structure. Geologic field mapping, reprocessing of 3D seismic reflection data, and soil gas surveys contributed to this effort.

Simmons, S. and Miller, J. Energy and Geoscience Institute at the University of Utah

Jul 01, 2019
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USGS Geophysics, Heat Flow, and Slip and Dilation Tendency Data used in Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geoph...

DeAngelo, J. et al Nevada Bureau of Mines and Geology

Jun 01, 2021
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3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...

Siler, D. and Pepin, J. United States Geological Survey

Oct 01, 2021
4 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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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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Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...

Moraga, J. et al Colorado School of Mines

Sep 01, 2020
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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
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