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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

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

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

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

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

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