OpenEI: Energy Information
  • Geothermal Data Repository
  • My User
    • Sign Up
    • Login
 
  • Data
    • View All Submissions
    • Data Lakes
    • Data Standards
    • Submit Data
  • Help
    • Frequently Asked Questions
    • Data Submission Best Practices
    • Data Submission Tutorial Videos
    • Contact GDR Help
  • About
  • Search

Search GDR Data

Showing results 1 - 9 of 9.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"stress measurement"×
Hydrothermal×

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

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

Oct 01, 2021
7.12 MB
Publicly accessible
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
Authors
Siler, D. and Pepin, J. United States Geological Survey
geothermalenergypca3d geologic modelgeologic modelgeologycharacterizationmachine learningmlbhsbrady hot springsprincipal component analysisproductionstressfaultsrbradyhydrothermalgeologic structureunsupervised3d well datacodegeothermicgeophysics

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

Passive Seismic Emission Tomography Results at San Emidio Nevada

Dec 01, 2016
66.54 MB
Publicly accessible
The utility of passive seismic emission tomography for mapping geothermal permeability has been tested at San Emidio in Nevada. The San Emidio study area overlaps a geothermal field in production since 1987 and another resource to the south of the production field. Passive seismic...
Authors
Warren, I. et al Ormat Technologies, Inc.
geothermalenergywholescalewaterholeobservationstresssystemspatialtemporalphysicsmodelinghydrologicthermalmechanicalgeospatial dataexcelp-wave velocity modelpassive seismicp-waveprocessed dataseismicvelocityhydrothermalsan emidiogeophysicspsetcharacteriztion

Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

Feb 07, 2023
Size unavailable
Publicly accessible
Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
Authors
Mordensky, S. et al United States Geological Survey
geothermalenergypfahydrothermalenergy assessmentresource assessmentretrospectivemachine learninggeosciencewestern usdata-drivenbias reductionfavorabilitymappingegslow tempprocessed dataresourcecharacterization

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

Hawthorne Nevada Deep Direct-Use Feasibility Study Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

Apr 05, 2020
4.1 MB
Publicly accessible
This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicl...
Authors
Ayling, B. and Hinz, N. Great Basin Center for Geothermal Energy
geothermalenergyhawthornegeochemistryconceptual modeltemperature logsborehole fracture datahawthorne army depotdirect usenevada2-meter temperaturesalteration mineralsptswell datafluid chemistryddutemperaturefracturexrdwater chemistrysurveycuttingsmodelingcapacityestimatesconceptualhwaad-2hwaad-3hwaad-2ageospatial datalow-tempertaurehydrothermalseservoireservoir compartmentalizationpower capacityimage log

Dixie Valley Engineered Geothermal System Exploration Methodology Project, Baseline Conceptual Model Report

Jan 02, 2014
504.96 MB
Publicly accessible
The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The overall project area is 2500km2 with the Calibration Area (Dixie Valley Geothermal Wellfield) being about 170km2....
Authors
Iovenitti, J. AltaRock Energy Inc
geothermaldixie valleyegshydrothermal systemfavorability/trust mappingfinal scientific reportegs exploration methodologybob karlingravitystation locationcomplete bouguer anomalyphil wannamakermagnetotelluricsmetadatadatainversionquantecileana tibulecseismic velocity modelfletcher h ibsergeostatisticsgeophysics

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
Google Map
  • About the GDR
  • Partners & Sponsors
  • Disclaimers
  • Developer Services
  • The GDR provides free access to data generated from projects funded by the U.S. Department of Energy's Office of Geothermal.
  • Content is available under Creative Commons Attribution 4.0 unless otherwise noted.

Privacy Policy Notification

This site uses cookies to store and share user preferences with other OpenEI sites, and uses Google Analytics to collect anonymous user information such as which pages are visited, for how often, and what searches or other webpages may have led users here. You can prevent Google Analytics from recognizing you on return visits to this site by disabling cookies on your browser or by installing a Google Analytics Opt-out Browser Add-on. By clicking "Accept" you agree this site can store cookies on your device and disclose information to OpenEI and Google Analytics in accordance with our privacy policy.

OpenEI Privacy Policy Google Analytics Terms of Service