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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: 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

EGS Collab Experiment 1: Microseismic Monitoring

Jul 29, 2019
2.83 TB
Publicly accessible
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...
Authors
Schoenball, M. et al Lawrence Berkeley National Laboratory
geothermalenergyegs collabsurfhydraulicfracturingstimulationsanford underground research facilityexperimentegsmicroseismic monitoringmeso-scale stimulationssandford underground researchmesoscale experimentscrystalline rock3d sensorleadsouth dakotasta/lta triggering algorithmmicroseismicitycatalograw dataprocessed databinary file interpreterpythongeospatial data

Soda Lake Geothermal: Raw 3D and 3C Seismic-Reflection Data from 2010 Survey

Sep 01, 2010
172.11 GB
Publicly accessible
This dataset contains seismic-reflection records created in 2010 around the Soda Lake geothermal field near Fallon, Nevada. The data was collected by the power plant operator at the time, Magma Energy (CYRQ Energy in 2024). This was a petroleum-industry-quality three-dimensional ...
Authors
N. Louie, J. et al University of Nevada Reno
geothermalenergysoda lake geothermalseismic dataraw data3dseismic reflectionseg-yfield logsproject reportssoda lakenevadavibroseisfallon3cshot recordsfield recordssurveyseismic surveymagmageophysics

Deep Direct-Use Feasibility Study Economic Analysis using GEOPHIRES for West Virginia University

Jan 09, 2020
3.73 MB
Publicly accessible
This dataset contains all the inputs used and output produced from the modified GEOPHIRES for the economic analysis of base case hybrid GDHC system, improved hybrid GDHC system with heat pump and for hot water GDHC. Software required: Microsoft Notepad, Microsoft Excel and GEOPHI...
Authors
Garapati, N. West Virginia University
geothermalenergygeophireswvulcohhybrid geothermal natural ags systemdirect-usereservoir simulationuncertainty analysisddudeep direct usefeasibilityeconomicgdhcdhsdistrict heatingdistrict heating and coolingcostheatlevelizedhot waterhybridheat pumpnatural gashybrid geothermal natural gas system

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

Jun 30, 2021
13.6 MB
Publicly accessible
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Authors
Buster, G. et al Upflow
geothermalenergymachine learningoptimizationoperationssynthetic datapower plantbig kahunagoomlgenetic optimizationforecastinputsoutputsconfigurationexamplephygnnphysics guided neural networkssteamfieldsteam fieldwellsflash plantsneural networkdataprocessed datacodepythonsimulationmodel

Alaska Geothermal Resource Data Gaps Analysis for Selected Regions

Jan 21, 2026
265.5 MB
In progress
Authors
Davalos Elizondo, E. et al National Laboratory of the Rockies
geothermalenergy

Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Jul 01, 2023
119.91 MB
Publicly accessible
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...
Authors
Yu, J. et al Pennsylvania State University
energyinduced seismicityegsutah forgewesterly graniteraw datacodematlabfault activationinjection testpressureflow ratereactivationshearfluid

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

Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems

Jan 31, 2022
1.45 GB
Publicly accessible
Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduct...
Authors
Hu, J. et al Lawrence Berkeley National Laboratory
geothermal bofieldenergymodelica buildings librarytoughcouplingdistrict energy systemdistrict heatingdistrict coolinggeothermalborefieldsimulationmodelmodelingoptimizationenergy storageseasonal energy storagegeothermal heat exchangeground source heat pumpgshpcodepythonmodelica

reV Geothermal Webinar Recording

Sep 29, 2026
Size unavailable
In progress
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 exclusionsrev

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

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

Utah FORGE 2-2446: Characterizing Stress Roughness Through Simulation of Hydraulic Fracture Growth

Jan 30, 2025
2.55 MB
Publicly accessible
This dataset covers work that investigated the apparent toughness anisotropy at Utah FORGE by comparing microseismic data with stress profiles from field measurements. The study analyzes the hydraulic fracture growth of Stage 3 at Well 16A(78)-32 using MEQ data, calibrating a nume...
Authors
Cusini, M. and Fei, F. Lawrence Livermore National Laboratory
geothermalenergyutah forgestress roughnesshydraulic fracturingmeqegsstress profilefield measurementshydraulic fracture growth16a78-32stage 3geostechnical reportprocessed datageophysics2-2446toughness anisotropyrock mechanics

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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