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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

Magnetotelluric Data Collected in 2016 over the San Emidio Geothermal Field in Nevada

This data set includes the magnetotelluric (MT) data collected from October 21 to November 9, 2016 over the San Emidio geothermal field in Nevada by Quantec Geoscience USA Inc. on behalf of US Geothermal Inc. as part of a project entitled "A Novel Approach to Map Permeability Usi...
Folsom, M. et al Ormat Technologies, Inc.
Nov 09, 2016
11 Resources
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Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All expe...
Yu, J. et al Pennsylvania State University
Jul 01, 2023
27 Resources
0 Stars
Curated

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
0 Stars
Curated
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