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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

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

Apr 20, 2020
6.74 MB
Publicly accessible
This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Authors
Chai, C. et al Oak Ridge National Laboratory
geothermalenergyegs collab3d seismic structuretransfer learningdeep learningmachine learninginteractivesurfp-waves-wavemicroseismic catalogseismic tomographyinteractive visualizationgeophysicsmodelingvelocitymodelmicroseismicitycatalogtransfer-learningdouble-difference tomography3dseismicmeqprocessed datageospatial data

Programs and Code for Subsurface and MultiSite Geothermal Exploration Artificial Intelligence

Sep 01, 2023
337.85 kB
Awaiting release
This dataset provides Python scripts supporting both subsurface and surface geothermal exploration AI models developed for the project "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning." It includes two main components: (1) scripts fo...
Authors
Demir, E. and Duzgun, S. Colorado School of Mines
geothermalenergygeothermal explorationsubsurfacesurfacemulti-siteartificial intelligenceaimachine learningmldeep learninghyperspectral imaging3d modeling2d classificationvoxel dataraster dataland surface temperaturemineral markersk-meansdata processingtensorflowpythoncodegpuexploration

Utah FORGE 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model

Jan 30, 2023
5.8 MB
Publicly accessible
This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation. A preliminary 3D velocity model for the larg...
Authors
Gritto, R. Array Information Technology
geothermalenergy3d seismic velocity modelseismic resolutionseismicgeophysicsreservoirmodelvelocityforgeutah forgeegscharacterizationreportpreliminarymilfordphasenetneural networkingmachine learningdeep learning

Utah FORGE: Source Imaging DAS-Based Seismic Event Catalog April 2024 Stimulation

Aug 26, 2025
140.41 kB
Publicly accessible
This catalog contains microseismic event locations recorded during the April 2024 stimulation at the Utah FORGE site. Events were detected and located using a DAS-specific source imaging workflow that avoids conventional phase picking. Instead, STA/LTA-transformed DAS and downhole...
Authors
Dvory, N. et al The University Of Utah
geothermalenergyforgeutahmicroseismic event locationsutah forgeuniversity of utahseismicaimachine learningdata-driven decisionscommunity safteyinfrastructure protectionproactive risk mitigationimproved safteyimmediate responsestimulationfracingground motionseismic hazardsegsevent catalogmlprocessed datareservoir characterizationapril 2024 stimulation

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

Hybrid machine learning model to predict 3D in-situ permeability evolution

Nov 22, 2022
5.58 MB
Publicly accessible
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Authors
Elsworth, D. and Marone, C. Pennsylvania State University
geothermalenergyegsnewberryhydraulicstimulationprocessed datamachine learningpermeability evolutionhydraulic fracturinginduced seismicityegs collabseismic data analysiswellhead pressureflow ratefracture permeabilitymicroearthquakeenhanced geothermal systems

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

Oct 01, 2021
7.12 MB
Publicly accessible
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
Authors
Siler, D. and Pepin, J. United States Geological Survey
geothermalenergypca3d geologic modelgeologic modelgeologycharacterizationmachine learningmlbhsbrady hot springsprincipal component analysisproductionstressfaultsrbradyhydrothermalgeologic structureunsupervised3d well datacodegeothermicgeophysics

INGENIOUS Great Basin Regional Dataset Compilation

Jun 30, 2022
116.98 MB
Publicly accessible
This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while re...
Authors
Ayling, B. et al GBCGE, NBMG, UNR
geothermalenergy2-meter probetemperaturegeochemistryquaternary falutsquaternary volcanicsgeodeticsseismicitypaleogeothermalwellsspringsslip and dilationingeniousplay fairway analysisgreat basinnevadautahidahocaliforniaoregonthermal conductivitymagnetotelluricsgravitymagneticsheat flowshapefilesgridssinterslipdilationearthquakesshearconductivityconductancegeotiffgeospatialcompilationdataregionaltufavolcanicsexplorationplay fairwaymodelingundiscovered systemsdiscoveryfavorabilityfaultsmachine learningelevation trenddetrended elevationseismic dataraw datasoda lake
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