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 - 3 of 3.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"nv"×
Labelled Training Data×

GIS Resource Compilation Map Package Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Jun 01, 2021
831.16 MB
Publicly accessible
This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups incl...
Authors
Brown, S. et al Nevada Bureau of Mines and Geology
geothermalenergynevadamachine learningmap packagegispcanmfbnnannelmgeochemistrygeophysicsheat flowslip and dilationstructureplay fairwaypfaexplorationcharacterizationgreat basindlipdilationgeodatabasehydrothermaldatamodelsprocessed datapaleo-geothermal featurestest sittessupervisedunsupervisedcultural

Utah FORGE: 2020-2021 Geothermal Energy/EGS Survey and Results

Jul 20, 2021
4.96 MB
Publicly accessible
The Utah FORGE project collaborated with the University of Utahs Department of Communication on a Capstone course during Fall Semester 2020. The course created a survey to gauge the general populations knowledge of geothermal energy and Enhanced Geothermal Systems (EGS). The surve...
Authors
Yeo, S. and McKasy, M. Energy and Geoscience Institute at the University of Utah
geothermalenergyegsgeothermal surveyegs surveyutah forgegeothermal knowledgeegs knowledgesurveyutahqualtricsraw datadatasurvey resultsconsent formquestionnairetraining data

Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

Sep 01, 2020
109.94 MB
Publicly accessible
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeothermal explorationhydrothermal mineral alterationsland surface temperaturefault densitypsinsarsubsidenceupliftbrady hot springsdesert peaknevadaconvolutional neural networkfallonmachine learningmodelhydrothermalmineraltemperaturerastergeospatial datageotifftraining datatraining dataset
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