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EGS Collab: 3D Geophysical Model Around the Sanford Underground Research Facility

Feb 06, 2019
14.13 MB
Publicly accessible
This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P and S-wave seismic speeds on a 3D grid. The file has six columns and provides latit...
Authors
Chai, C. et al Lawrence Berkeley National Laboratory
3d seismic structurejoint inversionblack hillssurfegs collab3dseismicmodelingmodelgeophysicsgeophysicaldensityvelocityspeedsanford underground research facilityinversionreservoir engineeringegscollabapiinteractivedata1dprofilemapvisualizationdepth2dp-waves-wave

Community Geothermal: Seward Alaska Heat Loop District Energy System Modelica Model

Sep 29, 2024
Size unavailable
In progress
This dataset contains a Modelica-based dynamic thermal simulation model of the Seward Heat Loop project. The model contains building loads generated from DesignBuilder simulations of the four city-owned buildings that are connected to the system. These buildings are heated by a hy...
Authors
Mitchell, M. et al National Renewable Energy Laboratory
geothermalenergyheat pumpocean sourcewell datacommgeo

Imperial Valley Dark Fiber Project Continuous DAS Data

Nov 10, 2020
1.09 TB
Publicly accessible
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...
Authors
Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory
geothermalenergydistributed acoustic sensingdasimperial valleybrawleyhidden geothermal resourcesearthquakesseismicitytectonicssouthern californiaseismic datastrain rateseismic noisedark fiberdark fiber dassalton searaw datageothermal explorationtelecommunications fiberpythonhdf5jupyter notebookgeophysicsfiber optich5py

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

Matlab Scripts and Sample Data Associated with Water Resources Research Article

Jul 18, 2015
487.87 MB
Publicly accessible
Scripts and data acquired at the Mirror Lake Research Site, cited by the article submitted to Water Resources Research: Distributed Acoustic Sensing (DAS) as a Distributed Hydraulic Sensor in Fractured Bedrock M. W. Becker(1), T. I. Coleman(2), and C. C. Ciervo(1) 1 California St...
Authors
Becker, M. and Coleman, T. California State University
geothermalenergydistributed acoustic sensingfractured rockmatlabboreholefse9silixa idasdasdistributed hydraulic sensinggeologyfracturedbedrockmirror lakewell dataraw datadisplacementfftdecimatedstep test

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

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

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 2-2446: Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity using Phase-Field Simulations

Jan 30, 2025
10.44 MB
Publicly accessible
This report presents a series of numerical experiments investigating the relationships among near-well fracture complexity, in situ stress conditions, and wellbore deviation. Using a phase-field modeling approach, the study explores how factors such as stress regimes, wellbore ori...
Authors
Cusini, M. and Fei, F. Lawrence Livermore National Laboratory
geothermalenergyutah forgephase fieldnumerical simulationnear wellbore fracture nucleationegsnear-wellfracture complexityin situ stresswellbore deviationphase-field modelingnumerical solutionsfracture nucleationgeos modelingstress regimesfracture propagationrock mechanicstechnical report

PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data

Mar 29, 2016
342.13 TB
Publicly accessible
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Authors
Feigl, K. et al University of Wisconsin
geothermalporotomodasfiber opticsurface sensorsseismic arraydistributed acoustic sensingporoeleastic tomographybradys geothermal fieldgeosciencedistributed sensingdownholetrenchedseismicityhydrothermalgeophysicsoediraw datajupyter notebookpythonhdf5hsdsh5pyh5pyd

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

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

Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests: Hydraulic Data

Jul 31, 2015
4.26 MB
Publicly accessible
Hydraulic responses from periodic hydraulic tests conducted at the Mirror Lake Fractured Rock Research Site, during the summer of 2015. These hydraulic responses were measured also using distributed acoustic sensing (DAS) which is cataloged in a different submission under this gr...
Authors
Cole, M. California State University
geothermalenergyperiodic hydraulic testsinterference testsdaspulse interference testsdistributed acoustic sensinghydraulic testingmatlabacoustic sensing data

Newberry Volcano Joint Active-Source and Teleseismic P-Wave Tomography Slowness Model and Processing Code

Dec 14, 2015
3.54 GB
Publicly accessible
This dataset contains a three-dimensional seismic slowness model and MATLAB processing code derived from P-wave seismic data collected at Newberry Volcano in central Oregon. The associated study combines active-source first-arrival travel times with teleseismic P-wave delay times ...
Authors
Heath, B. et al University of Oregon
geothermalenergynewberry volcanoseismic tomographyp-waveslownessslowness modelvelocity modelactive-source seismologyteleseismic delay timesjoint inversionupper crustmatlabdeepenprocessed datageophysicssuperhot

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-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

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

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
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