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Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2025 Workshop Presentation

Sep 18, 2025
70.48 MB
Publicly accessible
This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to esti...
Authors
Williams, J. GTC Analytics
geothermalenergyutah forgeegs2025 annual workshopinduced seismicitymachine learningrecurrent neural networksprobabilistic modelingseismic response predictionmagnitude-frequency analysisphysics-informed aipresentationpresentation recordingpresentation slidesreport

Utah FORGE 5-2419: Final Report and Presentation on Seismicity Permeability Relationships Probed via Nonlinear Acoustic Imaging

Sep 30, 2025
254.88 MB
Publicly accessible
This submission contains the final technical report and closeout presentation for Utah FORGE Project 5-2419, which investigates the coupled evolution of permeability and induced seismicity in enhanced geothermal systems using laboratory experiments, field observations, and nonline...
Authors
Elsworth, D. Pennsylvania State University
geothermalenergyutah forgeegspermeabilityinduced seismicitylaboratory experimentsfield observationsnonlinear acoustic imagingfault reactivationreservoir rockmicroearthquakestimulationphysics informed modelingmachine learningseismic momentstress statepermeability creationseismic hazardtechnical reportgeomechanicsgeophysicsmicroseismicity

Utah FORGE 6-3712: Report on Building a Recurrent Neural Network Framework for Induced Seismicity October, 2025

Oct 13, 2025
1.62 MB
Publicly accessible
This is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of designing a recurrent neural network (RNN) to predict induced seismicity. Background material is included t...
Authors
Williams, J. et al Global Technology Connection, Inc.
geothermalenergydeep learninginduced seismicitypredictivemagnitudeartificial intelligenceaimachine learningmldlphysics-basedmodelingutah forgeegstechnical reportseismic datainjection parametersgeophysical modelsprobabilistic

Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events

Jan 21, 2025
971.63 kB
Publicly accessible
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
Authors
Williams, J. et al Global Technology Connection, Inc.
geothermalenergyutah forgedata processingmachine learninginduced seismicitytechnical reportevent detectionmlartificial intelligenceaireal-timephysics informedrecurrent neural networksborehole seismicseismic datamicroseismicevent catalogmagnitude-frequency distributiongeophysicsegs

Utah FORGE 2-2439v2: A Multi-Component Approach to Characterizing In-Situ Stress Final Report

Dec 22, 2025
2.43 MB
Publicly accessible
This comprehensive technical report documents a multi-component approach to in-situ stress characterization at the Utah FORGE EGS site that integrates Machine Learning (ML) methods for predicting near-well principal stresses around geothermal wells with the physics-based finite el...
Authors
Bunger, A. et al University of Pittsburgh
geothermalenergyin-situ stress estimationutah forgewave velocitythermo-poro-elastic modelingmachine learningegsnear-wellbore stressfar-field principal stressstress anisotropyphysics-based modelingfinite element modelingsonic logtuvtechnical reportreservoir characterization

Utah FORGE 6-3712: Curated and Fused 2022 and 2024 Stimulation Injection Datasets and Processing Report February 2026

Feb 25, 2026
155 MB
Publicly accessible
This submission contains curated injection parameter datasets from the 2022 and 2024 stimulation experiments conducted at the Utah FORGE site, along with the report documenting the data processing workflow. The datasets were developed as part of Project 6-3712: Probabilistic Estim...
Authors
Williams, J. et al Global Technology Connection, Inc.
geothermalenergyinduced seismicityinjection parametersdatasetstimulationutah forgeegsstimulation experimentinjection datatreating pressureslurry rateclean ratecumulative injected volumeinflow rateflowbacktime-series dataprocessed datahydraulic stimulationfeomechanics

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

Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 May 2025

Jun 05, 2025
20.34 MB
Publicly accessible
These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and valida...
Authors
Lu, G. et al University of Pittsburgh
geothermalenergyutah16b78-32in-situ stressultrasonic velocityutah forgeegs16bmachine learningtrue triaxial testingsonic logsstress predictionfar-field stressthermo-poro-mechanicalmodelingdeep learningfinite element modelgeothermal reservoirstress profilingstress anisotropytechnical report

Utah FORGE 5-2615: Final Report for the Experimental Determination and Modeling-Informed Analysis of Thermo-Poromechanical Response of Fractured Rock

Jun 30, 2025
6.17 MB
Publicly accessible
This is the final technical report documenting laboratory experiments and modeling conducted to characterize the thermo-poromechanical behavior of fractured crystalline rocks for application to Utah FORGE. The report includes measurements of poroelastic and thermo-poroelastic prop...
Authors
Ghassemi, A. The University of Oklahoma
geothermalenergyutah forgeegslaboratory experimentstechnical reportthermo-poromechanicalfracturingporoelasticthermo-poroelasticpermeability evolutionhydraulic fracturedfitmodeling resultsstressfracture mechanicsgeomechanicsblock-scalebiot effective stressclosure pressurethermal stresstransverse fracturesstimulation

Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

Aug 30, 2024
973.4 kB
Publicly accessible
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Authors
Lu, G. et al University of Pittsburgh
geothermalenergyutah forgein-situ stress estimationphysics-based modelingfinite element methodmachine learning modelthermo-poro-mechanical effectwell loggingvelocity-to-stress relationshipmachine learningfemreporttechnical report16a78-32mlegs2-2439v2principal stressstress predictionfar-fieldpre-cooling

Utah FORGE: Hydraulic Fracture Width Determination Using Stoneley Wave Pressure Testing and Electrical Borehole Scans

Oct 06, 2023
1 MB
Publicly accessible
This report provides insights into Utah FORGE well 58-32's hydraulic fractures. It utilizes both electrical borehole scans from Schlumberger's Formation Micro-scanner Image tool (FMI) and Stoneley waves from a borehole sonic tool. These methods are combined in a comprehensive work...
Authors
Hornby, B. Hornby Geophysical Services, LLC
geothermalenergyfmistonely wavesformation micro-scanner image toolhydraulic fractureshydraulic fractureelectric borehole scansfracturesutah forgeutah forge well fracturespressure testingutah forge fracture reportborehole sonic toolegsfracture widthreportschlumbergerwave analysisworkflowfracture characterization58-32reservoir characterization

Project Data for Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers

Mar 31, 2026
601.08 MB
Awaiting release
This dataset contains project data generated by the project "Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers." It includes drilling, downhole drilling dynamics, bit records, daily drilling reports, directional surveys, lithology and mineralogy data, ...
Authors
Wriedt, J. and So, P. Geysers Power Company, LLC
geothermalenergydrillingthe geysersphysics-based drillingbit designgdc-36prati-44downhole drilling dynamicsbit recordsdirectional surveylithologymineralogymud logspason edrwell logssonic logsfmiubiwell schematicraw data

Utah FORGE 4-2541: Final Report and Presentation on Optimization and Validation of a Plug and Perf Stimulation Treatment Design

Jul 15, 2025
219.13 MB
Publicly accessible
This dataset contains the final technical report and closeout presentation for Utah FORGE Project 4-2541, which focused on the optimization and validation of a multistage plug and perf stimulation treatment design for enhanced geothermal systems. The report documents drilling, com...
Authors
Norbeck, J. Fervo Energy
geothermalenergyplug and perfstimulationutah forgeegshorizontal drillingmonitoring wellfiber-optic monitoringdistributed acoustic sensingdasdistributed temperature sensingdtspressuretemperaturestimulation performanceflow allocationfracture geometryinjectivityinduced seismicitytechnical reporthydraulic stimulation

Utah FORGE: 2024 Annual Report on Activities and Advancements

Jan 27, 2025
19.87 MB
Publicly accessible
This 2024 annual report for Phase 3B Year 2 at Utah FORGE provides an in-depth account of activities and advancements made at the site. Key achievements include drilling and stimulating the production well 16B(78)-32, creating a geothermal reservoir, and achieving commercial-scale...
Authors
McLennan, J. et al Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgephase 3byear 2yearly reportreportutah forge reportdrillingreservoir creationutah forge phase 3b report2024 annual reportegswell 16b78-32stimulationcirculationfiber optic monitoringdrilling technologiesseismic monitoringresearch and developmenttechnical reportannual report

Utah FORGE 3-2535: Final Report on Joint Electromagnetic, Seismic, and InSAR Imaging of Fracture Growth During EGS Resource Development

May 30, 2025
2 MB
Publicly accessible
This dataset contains the final technical report for the project Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development, carried out from 2021 to 2025 by Lawrence Berkeley Natio...
Authors
Alumbaugh, D. Lawrence Berkeley National Laboratory
geothermalenergyutah forgeegsseismicelectromageneticgeodeticdistributed fiber-optic sensingdata acquisitiondata processingdata interpretationtechnical reportinsarfracture growthfracture propertiesgeophysicsgeomechanics

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Apr 04, 2022
1.04 GB
Publicly accessible
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Authors
Ahmmed, B. Stanford University
geothermalenergymachine learningartificial intelligenceaiexplorationmodelmodelingprocessed datatraining datatraining datasetremote sensinghidden geothermal resourcesresource detectiondiscoverydevelopmentresourceneural networkprediction

Utah FORGE 5-2557: Fluid and Temperature in Fracture Mechanics and Coupled THMC Processes 2025 Workshop Presentation

Sep 18, 2025
106.89 MB
Publicly accessible
This is a presentation on the Role of Fluid and Temperature in Fracture Mechanics and Coupled Thermo-Hydro-Mechanical-Chemical (THMC) Processes for Enhanced Geothermal Systems project by Purdue University, presented by Distinguished Professor of Physics & Astronomy, Dr. Laura J. P...
Authors
Pyrak-Nolte, L. Purdue University
geothermalenergyutah forgeegs2025 annual workshopfracture mechanicsthmcfluid-rock interactionsrate-and-statefrictioncoulomb failureseismicaseismicgeomechanicspresentationpresentation recordingpresentation slidesreport

Utah FORGE 5-2615: Laboratory Data for Insights on Hydraulic Fracture Closure and Stress Measurement

Jun 12, 2024
4.82 MB
Publicly accessible
This dataset includes data from injection/fall-off experiments conducted in controlled laboratory settings. The aim is to investigate the physics governing fracture closure and the associated stress measurements during hydraulic fracturing. These time series data include flow rat...
Authors
Ye, Z. and Ghassemi, A. University of Oklahoma
hydraulic fracturinginjection/fall-off testsin-situ stress measurementsfracture closuregeothermalegsutah forgeminifracstressflow ratepressurevolumelaboratoryenergyinjectionfall-offwater injectionoil injectionsierra white granitecrab orchard sandstonescioto sandstonekismetgeomechanics

Simulation Tools for Modeling Thermal Spallation Drilling on Multiple Scales

Jan 01, 2012
633.76 kB
Publicly accessible
Widespread adoption of geothermal energy will require access to deeply buried resources in granitic basement rocks at high temperatures and pressures. Exploiting these resources necessitates novel methods for drilling, stimulation, and maintenance, under operating conditions that ...
Authors
Walsh, S. et al Lawrence Livermore National Laboratory
geothermalthermal spallation drillingnumerical modelingengineered geothermal systemsegsgranitic basement rocksfluid dynamicsheat transfergrain-scale thermomechanicsunified tool

Salton Sea Geothermal Development Nontechnical Barriers to Entry Analysis and Perspectives

Jun 28, 2022
5.95 MB
Publicly accessible
The report included in this submission details the nontechnical barriers to entry for development of geothermal resources in the Salton Sea. The Salton Sea provides an economically viable opportunity for replacing the energy imported by California which makes up 25 percent of Cali...
Authors
Goodman, D. et al Pacific Northwest National Laboratory
geothermalenergysalton seatechnoeconomic analysismageteanontechnicalbarrierslithiumresource developmentresourcecaliforniatechnoeconomictechno economictechno-economicanalysismodeldevelopmentfeasibilityreportresource potentiallithium extraction

Utah FORGE: Laboratory Shear Experiments Linking Fault Roughness, Friction, Permeability, and P-Wave Characteristics

Aug 20, 2025
23.22 GB
Publicly accessible
This dataset contains results from five laboratory shear experiments on gneiss and granitoid samples from the Utah FORGE site, conducted at Penn State University. The experiments investigate links between fault surface roughness, frictional behavior, permeability, and P-wave acous...
Authors
Eijsink, A. et al Pennsylvania State University
geothermalenergyfrictionroughnessutah forgeegslaboratory datamodeled datashear experimentsfault mechanicspermeabilityp-waveacoustic transmissivityfault roughnessrate-and-state frictionbiaxial deformationgneissgranitoidoptical profilometrykeyencersfit3000mechanical dataacoustic datafault zone propertiesgeomechanicsrock physicsgeothermal reservoir characterization

Seismic Survey 2016 Metadata at San Emidio, Nevada

Dec 05, 2016
54.86 MB
Publicly accessible
1301 Vertical Component seismic instruments were deployed at San Emidio Geothermal field in Nevada in December 2016. The first record starts at 2016-12-05T02:00:00.000000Z (UTC) and the last record ends at 2016-12-11T14:00:59.998000Z (UTC). Data are stored in individual files in o...
Authors
Lord, N. et al University of Wisconsin
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalseismicseismicitydatametadatasurveynevadareporttechnical specificationintrumentationspecsspecspecifications

WHOLESCALE: Seismic Survey Data from San Emidio Nevada 2021

Apr 06, 2021
1.67 TB
Publicly accessible
This dataset includes raw and processed seismic data from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 N, 119.409019 W. The first...
Authors
Lord, N. et al University of Wisconsin Madison
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalsacraw dataprocessed datageophysicssiesmic datasmartsolodatacubeseismographdata lakesan emdidionevadapumpingtri-axialdld

Snake River Plain FORGE: Site Characterization Data

Apr 18, 2016
632.32 MB
Publicly accessible
The site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. This collection includes data on seismic events, groundwater,...
Authors
Moos, D. and Barton, C. Idaho National Laboratory
geothermalforgeegssrgcsnake river plainidahosite characterizationsite datageologic modelgeomechanical modelwell datatempsupplementaladdendum3d modelrock physicsinel-1wo-2usgs-142websiteeventsinformationblogdatacollectionpaperstressinel sitestrian ratesdeformationanalyticalmodelinlseismicmonitoringannual reportmapseismic modelinggeologichistorysettingsublithosphericneogeneyellowstoneheisepicabovolcanicfieldvoncanicgravityheat flowcalderavolcanismmantle plumeoceanic hotspotmagmatismgrraesrpeastern snake river plainbasinpotentialsiteextensionsubsidencepaleoseismologyextensional structuresintrusiontectonic faultsgeomechanicalcharacterizationheheliumisotopeisotopic evidenceundiscoveredgeothermal systemserspaquiferthermal watermodelingthermalgeochemicalanomaliesconceptual modelwellboregroundwatertemperaturedistributionwell headstdtarget depthlocationcoordinateselevationresidualisostaticmagneticusgsmagneticsnrmeasternmtinversionlong-periodphase 1resistivityelectricalsoundinggeoelectricsectionrefraction surveyteleseismicreceiverprofilingrefractionray trace3dvolcanicspaleozoicrhyoliticpetreljewelsuitefold hingessnapshotsrpsrgmagnetotellurics

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
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