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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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TEAMER: Vertical Axis Hydrokinetic Turbine Array Modeling And Optimization Data
This dataset from Emrgy Inc., in collaboration with Sandia National Laboratories, includes integration of modular vertical axis hydrokinetic (HK) turbines into a higher fidelity canal hydraulic model. This submission contains all data collected and used for the Vertical Axis Hydro...
Cuthbert, T. Emrgy, Inc.
Jul 31, 2024
34 Resources
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34 Resources
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Publicly accessible