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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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Utah FORGE: Well 16A(78)-32 Drilling Data
This dataset includes survey data, drilling data, daily reports, summaries of daily operations, and rig photos from the drilling of Utah FORGE well 16A(78)-32, which is a highly deviated deep well. It was completed 60 days ahead of schedule.
Rig move in began 10/22/2020 and dril...
McLennan, J. et al Energy and Geoscience Institute at the University of Utah
Jan 08, 2021
15 Resources
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15 Resources
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EGS Collab Experiment 1: Microseismic Monitoring
The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...
Schoenball, M. et al Lawrence Berkeley National Laboratory
Jul 29, 2019
46 Resources
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46 Resources
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Subsurface Geological Information and Models in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy
This purpose of this set of entries is to group together the materials and analytical methods used in the assessment of the natural rock properties within and surrounding two potential reservoirs.
Jordan, T. et al Cornell University
Oct 27, 2019
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27 Resources
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