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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

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

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

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

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

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

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

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

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: 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