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
    • Instructions for Funds Recipients
    • Data Provision Guidelines
    • Contact GDR Help
  • About
  • Search

Search GDR Data

Showing results 1 - 4 of 4.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Technologies
Featured Projects
Topics
Data Type
"thermomechanical processes"×
Geology×

University of Illinois Campus Deep Direct-Use Feasibility Study Geological Characterization of the Mt. Simon Sandstone

These studies undertook detailed analyses of the Mt. Simon Sandstone in the Illinois Basin for geological storage and sequestration, and brine extraction.
Lin, Y. et al University of Illinois
Mar 30, 2018
5 Resources
0 Stars
Publicly accessible

University of Illinois Campus Deep Direct-Use Feasibility Study Regional Geology

Links to papers and reports describing the structure and character of the Illinois Basin geology. Included are descriptions of the two reservoirs that are being modeled for the DDU feasibility project at University of Illinois, the St. Peter and Mt. Simon Sandstones.
Lin, Y. et al University of Illinois
Mar 30, 2018
4 Resources
0 Stars
Publicly accessible

Remote Sensing and Geology of Glass Buttes, Oregon

This data set includes Light Detection and Ranging (LiDAR) data, a remote sensing processing report, and a geologic map of the Glass Buttes study area for ORMAT. The total area flown for the LiDAR remote sensing was 86,631 acres to fully encompass the area of interest (84,849 ac...
Akerley, J. et al Ormat Nevada Inc
Jun 21, 2010
3 Resources
0 Stars
Publicly accessible

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

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...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
Publicly accessible
  • About the GDR
  • Partners & Sponsors
  • Disclaimers
  • Developer Services
  • The GDR is the submission point for all data collected from research funded by the U.S. Department of Energy's Geothermal Technologies Office.
  • 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