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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

QuakeCastNet: Source Code for Forecasting of Injection-Induced Seismicity

Sep 20, 2026
16.21 MB
Curated
This submission houses the companion code for the manuscript by Zhengfa Bi (Lawrence Berkeley National Laboratory) and Nori Nakata (Lawrence Berkeley National Laboratory; MIT). Both the companion code and manuscript are included in the resources section of this submission. Fluid ...
Authors
Nakata, N. and Bi, Z. Lawrence Berkeley National Laboratory
geothermalenergyutah forgeseismicitydeep learningthe geysersforecastegsinduced seismicityseismicity forecastingtftprobabilisticmulti-horizontemporal transformer frameworkmachine learningdecision supporttraffic light

Renewable Energy Potential Model: Priority Geothermal Leasing Areas ReEDs Results

May 20, 2024
859.13 kB
Publicly accessible
This dataset contains the results of a study conducted by the National Renewable Energy Laboratory (NREL) to identify potential future priority geothermal leasing areas on Bureau of Land Management (BLM) and United States Forest Service (USFS) lands. The analysis uses the Regional...
Authors
Smith, F. et al National Renewable Energy Laboratory
geothermalenergyreedsgamspythonblmusfsrenewable energy potential modelgeothermal leasing areaspriority leasingresource potentialfeasibilitytechnology combinationnatural resource conflictstransmissiongeothermal capacitygenerationsystem costemissionstechnical reportprocessed datamodelinggithubmodel results

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

Programs and Code for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
710.72 kB
Publicly accessible
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Authors
Moraga, J. Colorado School of Mines
geothermalenergycodershell scriptsgeothermal aimachine learningself organizing mapk-meanspythonaiartificial intelligencedeep learningexplorationgeothermal explorationremote sensingblindsite detectionlstland surface temperaturenumpyrastertensorflowk meananomaly detectionlandsat adr lstsbatchslurmshell

Utah FORGE: Triggered 3-Component Surface Nodal Seismic Waveforms from the April 2022 FOAL 1 Experiment

Jun 30, 2026
736.6 MB
Publicly accessible
This package contains triggered 3-component surface nodal seismic waveforms recorded during the FOAL 1 experiment, or FORGE Observation Array Linear #1, which occurred during the April 2022 hydraulic stimulation of well 16A(78)-32 at the Utah FORGE EGS site. This data was utilized...
Authors
Kim, J. et al Rice University
geothermalenergyegsutah forgeforgemicroseismichydraulic stimulationfoal 1forge observation array linear16a32-32april 2022microseismicityinduced seismicitypassive seismic monitoringsurface nodal array3-component seismic datasmartsolominiseedstationxmlevent catalogwell trajectoryfogmoregeophysicsseismic dataprocessed data

Utah FORGE: Triggered DAS and Continuous Downhole Geophone Data from April 2024 Stimulations

Apr 01, 2024
35.23 TB
Publicly accessible
This dataset contains distributed acoustic sensing (DAS) and downhole geophone data collected during the April 2024 stimulation experiments at the Utah FORGE site. DAS data were acquired from well 16B(78)-32 by Neubrex and processed by GeoEnergie Suisse (GES), covering the period ...
Authors
Dyer, B. et al Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgeegsdasdistributed acoustic sensingseismictriggered eventsgeophonesdownholedownhole seismicneubrexgeoenergie suissegesaprill 2024stimulationhydraulic fracturingcountinuous dataraw dataprocessed datageophysics58-3216b78-3256-32monitoring well

reV Geothermal Webinar Recording

Sep 29, 2026
Size unavailable
Curated
This recorded webinar provides background on National Laboratory of the Rockies reV model (https://www.nlr.gov/gis/rev) and specifically the geothermal module. The reV model is a first-of-its-kind detailed spatio-temporal modeling assessment tool that empowers users to calculate e...
Authors
Trainor-Guitton, W. et al National Laboratory of the Rockies
geothermalenergytechnical capacityland exclusionsrevnlrmodelingenergy capacitygenerationsupply curvegridinfrastructureland-usegeothermal analysiswebinarvideo recordingsystem costspatio-temporal

Pilgrim Hot Springs: GEOPHIRES Inputs and Outputs for Direct-Use Geothermal District Heating and Cooling

Mar 21, 2024
211.86 kB
Publicly accessible
This dataset includes files for a techno-economic analysis conducted using the GEOPHIRES simulator to examine the feasibility of expanding a larger district heating site in a remote location: Pilgrim Hot Springs, Alaska. Files included here are GEOPHIRES inputs and outputs for fiv...
Authors
Pauling, H. et al National Renewable Energy Laboratory
geothermalenergygeophireschporcparallel cycletopping cyclepilgrim hot springsalaskatechno-economic analysisfeasibilityteareservoir simulationsheat demandcapitaloperating costsdistrict geothermaldistrict heatingmodelmodelingpythongithubinputsoutputs

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

Apr 15, 2022
113.79 MB
Publicly accessible
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...
Authors
Jin, W. et al Idaho National Laboratory
reservoir thermal energy storagestochastic simulationgeotesmachine learningmodelingtesht-rtescharacterizationnumerical modelstochastichydrogeologic formationsimulated datasimulation datahigh-temperaturethermal energy storageoptimizationartificial neural network regressionannneural networkoperation scenariosseasonal-cyclepareto frontsseasonal operationcontinuous operationfalconmoose
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