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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: Triggered DAS and Continuous Downhole Geophone Data from April 2024 Stimulations

Apr 01, 2024
35.23 TB
Publicly accessible
This dataset contains distributed acoustic sensing (DAS) and downhole geophone data collected during the April 2024 stimulation experiments at the Utah FORGE site. DAS data were acquired from well 16B(78)-32 by Neubrex and processed by GeoEnergie Suisse (GES), covering the period ...
Authors
Dyer, B. et al Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgeegsdasdistributed acoustic sensingseismictriggered eventsgeophonesdownholedownhole seismicneubrexgeoenergie suissegesaprill 2024stimulationhydraulic fracturingcountinuous dataraw dataprocessed datageophysics58-3216b78-3256-32monitoring well

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

Cape EGS: Seismic Attenuation Profile and DAS Microseismic P-wave Spectra

Mar 17, 2026
15.25 GB
Publicly accessible
This dataset contains a 1D P-wave attenuation (Q) profile, distributed acoustic sensing (DAS) microseismic P-wave spectra, and derived source parameters from the Delano 1OB well at the Cape Modern geothermal field. The data were collected during a stimulation period from mid-Febru...
Authors
Chang, H. et al Lamont Doherty Earth Observatory
geothermalenergydasfiber-opticattenuationmicroseismicityp-wavesource parametersstress dropcapeforgeqspectraseismicegscape modernutah forgedistributed acoustic sensingp-wave attenuationquality factorbrune modelcorner frequencyseismic momentmoment magnitudewell logsdownhole measurementsraw dataprocessed datageomechanicsgeophysics

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

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
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  • The GDR provides free access to data generated from projects funded by the U.S. Department of Energy's Office of Geothermal.
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