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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Mar 29, 2021
179.87 MB
Publicly accessible
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Authors
Vesselinov, V. Los Alamos National Laboratory
geothermalenergymachine-learningnew mexicobradynevadagreat basinsouthwest new mexicomulti-physicsbrady hot springssmarttensorsgeothermalcloudgeothermal cloudlos alamos national laboratorysite datasimulationmachine learningmodel

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

Literature Collection for the Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers

Jan 20, 2026
Size unavailable
Publicly accessible
This submission contains links to multiple publications on the Evaluation Of Physics-Based Drilling and Alternative Bit Design At The Geysers. The long-term goal of the project was to safely implement oil and gas industry drilling best-practices, particularly with respect to limit...
Authors
Wriedt, J. Geysers Power Company, LLC
geothermalenergygeyserspublicationsphysics-based drillingbit designlimiter redesignelectronic drilling recordsbit technologycontrol strategies

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 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

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

PoroTomo: Horizontal Distributed Acoustic Sensing (DAS) Measurements During an M 2.3 Explosion

Dec 18, 2018
198.67 GB
Publicly accessible
Included here are Distributed Acoustic Sensing (DAS) data collected by the horizontal DAS array at Brady's Hot Springs Geothermal Field. The system recorded this data during an M 2.3 explosion at the Nevada Test Site (NTS), which is located approximately 400km southeast of the fie...
Authors
Kratt, C. et al Center for Transformative Environmental Monitoring Programs (CTEMPs)
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicaldasbradys hot springsdtsporotomoseismicgeophysicsdas datasgyseg-ydistributed acoustic sensingdistributed temperature sensinghydrothermaltrenchedsurface sensorsseismicityraw data

Utah FORGE: GeoThermOPTIMAL Presentation Video

Dec 12, 2022
20.69 MB
Publicly accessible
This is a project description video by Dr. William W. Fleckenstein related to their "Development of Multi-Stage Fracturing System and Wellbore Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores" R&D project at Utah FORGE which is linked...
Authors
Fleckenstein, W. Colorado School of Mines
geothermalenergyutah forgeforgemulti-stage fracturingwellbore tractorzonal isolationhorizontal drillingfracturingegsfracingwell stimulationvideoutahdrillingtechnologywellbore technologiessleevesmp4stimulation

Stanford Thermal Earth Model for the Conterminous United States

Mar 14, 2024
21.57 GB
Publicly accessible
Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Authors
Aljubran, M. and Horne, R. Stanford University
thermal earth modeltemperaturegeothermalenergystanfordtemperature-at-depthheat flowrock thermal conductivityinterpignnphysics-informedgraph neural networksmachine learningmodeltemperature modelarcgisapimodel inputsmodel outputsdata-drivenspatial interpolationalgorithmheat conductionbottomhole temperature

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

WHOLESCALE: Mass Flux Rates for Wells at San Emidio in December 2016

Dec 01, 2016
1.79 MB
Publicly accessible
This dataset provides mass flux rates in kg/s from six (production and injection) wells at San Emidio at minute intervals from December 1, 2016 December 15, 2016. Files for injection wells are named with "IW", for instance "WellIW42-21SI.csv", and include negative flux rates. Fil...
Authors
Cardiff, M. et al University of Wisconsin Madison
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalgeophysicssan emidionevadamass flux ratesflow rateswell datainjectionproduction

EGS Collab Experiment 2: Distributed Fiber Optic Acoustic Data (DAS)

May 28, 2024
212.2 TB
Publicly accessible
Distributed fiber optic sensing was an important part of the monitoring system for EGS Collab Experiment #2. A single loop of custom fiber package was grouted into the four monitoring boreholes that bracketed the experiment volume. This fiber package contained two multi-mode fiber...
Authors
Rodriguez Tribaldos, V. and Hopp, C. Lawrence Berkeley National Laboratory
geothermalenergyegs collabexperiment 2distributed acoustic sensingdassilixaidasterra15trebleoptasenseodh3hdf5tdmsraw datastrain ratemulti-mode fibersingle-mode fibergeophysics

Peer Review Presentation: Blind Geothermal System Exploration in Active Volcanic Environments

May 19, 2010
910.73 kB
Publicly accessible
Geothermal Technologies Program Peer Review Presentation on Blind Geothermal System Exploration in Active Volcanic Environments. Includes plans and statuses for multi-phase geophysical and geochemical surveys in overt and subtle volcanic systems in Hawaii and Maui.
Authors
Martini, B. Ormat Nevada Inc
geothermalexplorationblind geothermal systemsmauihawaiivolcanicgeophysicalgeochemicaltimelinebudgetgravityco2 fluxsoil temperaturehyperspectralisotopeaeromagneticpunaulupalakuahaleakalarift zone

Development of a Downhole Tool Measuring Real-Time Concentration of Ionic Tracers and pH in Geothermal Reservoirs

Mar 31, 2014
Size unavailable
Publicly accessible
For enhanced or Engineered Geothermal Systems (EGS) geothermal brine is pumped to the surface via the production wells, the heat extracted to turn a turbine to generate electricity, and the spent brine re-injected via injection wells back underground. If designed properly, the sub...
Authors
Hess, R. et al Sandia National Laboratories
geothermalegsdownhole toolreservoir monitoringchemical tracershigh temperature electrochemical sensorhigh temphigh temperatureelectrochemical sensorionic tracersengineered geothermal systems egssandia national labssnldoi 10.1117/12.2051151tracerdownholehigh pressure

WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021

Jan 12, 2021
857.7 MB
Publicly accessible
This submission contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in ...
Authors
Kleich, S. et al University of Wisconsin Madison
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalsan emidionevadarock samplesfieldsamplessamplerock samplegeologyimagesphotoscore samples

WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021 Version 2.0

Jan 12, 2021
21.28 kB
Publicly accessible
This submission includes an update to the WHOLESCALESamples2021January.xls file where the strikes and dips initially reported have been corrected to comply with the right hand rule. The updated excel file and a link to the original submission are included in this report. The ori...
Authors
Kleich, S. et al University of Wisconsin Madison
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalsan emidionevadarock samplesgeologyimagesphotoscore samplesgeophysicssamplesrockraw data

EGS Collab Experiment 1: DNA tracer data on transport through porous media

Nov 21, 2020
34.37 kB
Publicly accessible
This submission contains DNA tracer data that supports the analysis and conclusions of the publication, "DNA tracer transport through porous media The effect of DNA length and adsorption." https://doi.org/10.1029/2020WR028382. This experiment used DNA as an artificial reservoir t...
Authors
Zhang, Y. et al Stanford University
tracergroundwaterdnamulti-well tracer testgroundwater tracingartificial tracerdataraw dataadsorptionreservoir tracerartificial reservoir tracerhydrogeologyhydrologycolumn transportexperimentlablaboratorylab data

FedGeo Project: Low-Temperature Geothermal Resources at the U.S. Army Detroit Arsenal, Warren, Michigan

Sep 29, 2026
102.51 MB
In progress
This collection includes datasets used for the analyses and modeling of low-temperature geothermal resources at the U.S. Army's Detroit Arsenal located in Warren, Michigan. This project file includes tabular and geospatial data accessed from publicly available repositories held by...
Authors
University of Illinois Urbana-Champaign
geothermalenergydetroit arsenalmichiganmodelinggeophysicsdrillingfedgeogeologyhydrogeologylow temperature

Seismic Survey 2016 Data at San Emidio Nevada

Jan 05, 2016
2.57 TB
Publicly accessible
Included here are seismic data recorded at the San Emidio Geothermal field in Nevada. This passive seismic data were collected as part of the DOE-funded Subsurface Technology and Engineering R&D (SubTER) project to advance imaging and characterization of geothermal permeability. ...
Authors
Lord, N. et al University of Wisconsin Madison
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalseismicseismicitydatametadatasurveynevadasegdmseedminiseedsan emidiohydrothermalcharacterizationgeophysicspassive seismic

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

Geologic Reservoir Content Model from Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

Sep 30, 2015
2.03 MB
Publicly accessible
This dataset contains the known hydrocarbon reservoirs within the study area of the Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB) as part of Phase 1, Natural Reservoirs Quality Analysis. The final values for Reservoir Productivity Index (RPI) and uncertainty...
Authors
E., T. Cornell University
geothermalappalachian basinnew yorkpennsylvaniawest virginiareservoirproductivityreservoir productivity indexrpigpfa-abgeothermal play fairway analysisdistrict heatingdeep direct uselow-temperaturepennslyvaniageologic reservoirsporositypermeabilityfavorabilitypfacontent modelngds content modelusgin content modelaasg geothermal datageologic reservoireasternusaeastcharacterizationnaturalresourcelow temperaturegeologyuncertainty

Cape EGS and Utah FORGE: Empirical 3D Seismic Velocity Model

Nov 12, 2025
1.08 GB
Publicly accessible
This dataset provides an empirical three-dimensional P and S-wave velocity model covering a 30 x 30 km area and extending to 10 km depth around the Cape Modern EGS and Utah FORGE sites. It incorporates three-dimensional topography and a sediment/basement contact derived from geoph...
Authors
Nakata, N. et al Lawrence Berkeley National Laboratory
geothermalenergyvelocitycape modernseismicseismic velocityvelocity modelp-waves-waveutah forgeenhanced geothermal systemsegscape egssubsurface characterizationnetcdfborehole velocityempirical model3d model

GOOML Kahunanui Data Curation, Historical Modeling, Forecast Modeling, and Genetic Optimization Examples

Jan 30, 2023
725.34 MB
Awaiting release
This dataset contains example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) framework, specifically for the fictional Kahunanui (KHN) geothermal power plant. The dataset includes synthetic time series data, confi...
Authors
Taverna, N. et al Upflow
geothermalenergymachine learninggoomlpower plantoptimizationgenetic optimizationregressionneural networkoperationssynthetic datakahunanuiforecasthindcastdata curationinputsoutputsconfigurationexamplephygnnphysics guided neural networkssteamfieldsteam fieldwellsflash plantsprocessed datapythonjupyter notebookmodelmodelingcode

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

Model results and data for Nontechnical Barriers to Geothermal Development

Jul 25, 2022
73.96 kB
Publicly accessible
Data included in this submission support the analysis conducted for the report "Nontechnical Barriers to Geothermal Development" which is linked bellow. These data include information about the power purchase agreements (PPAs) analyzed for the report, inputs and model results for ...
Authors
Rabinowitz, H. et al Pacific Northwest National Laboratory
geothermalenergyppapro formanontechnical barriersexcelprocessed dataostipower purchase agreementfeasibilityeconomiccostregression analysisassessmentu.s. department of energy office of scientific and technical informationelectricitypower production
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