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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
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Fallon FORGE: Well Data, Geophysical Data, and Geologic Maps

The data is associated to the Fallon FORGE project and includes mudlogs for all wells used to characterize the subsurface, as wells as gravity, magnetotelluric, earthquake seismicity, and temperature data from the Navy GPO and Ormat. Also included are geologic maps from the USGS a...

Blankenship, D. Sandia National Laboratories

Mar 31, 2016
54 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

Fallon FORGE: Well Data, Geophysical Data, and Geologic Maps