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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

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

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Oct 20, 2021
6.41 MB
Publicly accessible
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Authors
Beckers, K. et al National Renewable Energy Laboratory
geothermalenergymachine learningmlsubsurfacecharacterizationbrady hot springsbhspredictionreservoir modelingtime seriespcaprincipal component analysisreservoir managementreservoirdual-porositystimulationinjection testpdetemperatureflowpressuresimulationsingle-fracturedoubletheat maptensorflowcnnlstmmlphydrothermalopen source reservoirosrnevada

Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment

Nov 07, 2023
12.98 MB
Publicly accessible
Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding...
Authors
Roseboom, M. et al Pennsylvania State University
geothermalenergyinduced seismicityinjection rateegsseismic momentgeomechanicsgeophysicsutah forgeshearmatlabshear experimentsraw datacodecore experimenttemcoconfining pressurepore pressureaxial pressureshear displacementfracturealong-fault pressureconstant shear stress

Utah FORGE: Fluid Injection-Rate Controls on Seismic Moment from Laboratory Fault Reactivation Experiments

Sep 16, 2025
5.43 GB
Publicly accessible
This dataset contains experimental and acoustic data from shear reactivation tests that investigate the relationship between fluid-injection rate, pore pressure distribution, and seismic moment during laboratory fault slip. It includes raw mechanical data and acoustic emission rec...
Authors
Elsworth, D. et al Pennsylvania State University
geothermalenergyinduced seismicityegsgeomechanicsutah forgegranitoidlaboratory experimentsfault reactivationshear slipfluid injectioninjection ratepore pressurepore pressure distributionseismic momentacoustic emissionspermeabilitytriaxial testingshear stressaxial displacementpressure vesselmechinical datatime-series dataraw dataprocessed datamatlab