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Utah FORGE: Phase Native State FALCON Model Files

Jun 06, 2019
11.78 MB
Publicly accessible
The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...
Authors
Podgorney, R. Idaho National Laboratory
geothermalenergyfalconforgenative stateutahroosevelt hot springsmilfordegsenhanced geothermal systemengineered geothermal systemutah forgecodesimulationscprocessed datapreprocessed dataraw datageospatial data3-d modellinggeologytemperaturestresspressurecharacterizationmodeling3-d modelinglithologymesh fileinputslithologic contacts

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

Oct 01, 2021
5.68 MB
Publicly accessible
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...
Authors
Siler, D. et al United States Geological Survey
geothermalenergynmfkbrady hot springsmachine learningmlbhsnonnegative matrix factorization k-meanshydrothermalbradyk-meansclusteringnonnegative matrix factorizationmatrix factorizationgeothermalcloudsmarttensorsunsupervised3d well data3d geologic mapgeologic structurefaultsstressgeologycharacterizationgeologic modelproductioncode