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 - 8 of 8.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"production profile"×
Remote Sensing×

Lightning Dock Geothermal Field Data Package, Hidalgo County, New Mexico

Aug 19, 2026
7.4 GB
Publicly accessible
This submission is a curated geoscience, well and plant-operations data package for the Lightning Dock geothermal field in the Animas Valley, Hidalgo County, south-western New Mexico, a liquid-dominated system produced for binary (ORC) power generation. It covers well-by-well data...
Authors
Ifrene, G. et al Zanskar Geothermal
lightning dockwell logsgisproduction datageothermalenergytracer testpower generationgeochemistrygeophysicsgroundwaterbinary systemorcdownhole temperaturebouguermagnetotelluricinversion modelsaeromagneticsgravity surveylidarquaternary faultgeologymud logstemperature

Utah FORGE 3-2535: Compilation of Geodetic Data and Estimation of Associated Deformation

Apr 29, 2022
17.77 MB
Publicly accessible
Report on possible geodetic signature of the 3 stimulations in April 2022 as well as a comparison with existing InSAR data gathered over the site before, during, and after the stimulation. In geothermal production it is important to understand the existing stress field and the cha...
Authors
Vasco, D. et al Lawrence Berkeley National Laboratory
geothermalenergyinsarground deformationcompressional velocity modelegsremote sensingwell characterizationwell 16awell 16butah forge

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Apr 04, 2022
1.04 GB
Publicly accessible
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Authors
Ahmmed, B. Stanford University
geothermalenergymachine learningartificial intelligenceaiexplorationmodelmodelingprocessed datatraining datatraining datasetremote sensinghidden geothermal resourcesresource detectiondiscoverydevelopmentresourceneural networkprediction

Utah FORGE 3-2535: Numerical Modeling of Energized Steel-Casing Source for Imaging Stimulated Zone

Nov 15, 2022
885.78 kB
Publicly accessible
This short report details and tests the workflow that will be used to simulate steel well casings in deviated production/extraction boreholes at at the Utah FORGE site. Boreholes will be electrically energized and will serve as data sources for future proposed electromagnetic bore...
Authors
Um, E. et al Lawrence Berkeley National Laboratory
geothermalenergyegsremote sensingwell characterizationutah forgewell 16awell 16b

Utah FORGE 3-2535: Modeling Studies of Energized Steel-Casing Source EM Method for Detecting Stimulated Zone

Feb 06, 2023
6.08 MB
Publicly accessible
Numerical modeling Studies for electromagnetic (EM) Data Acquisition Survey Design this milestone report describes the 3D modeling studies of energized steel-casing source electromagnetic method for detecting stimulated zone at the Utah FORGE Site. FORGE project 3-2535 is planning...
Authors
Um, E. et al Lawrence Berkeley National Laboratory
geothermalenergyutah forgeegsremote sensingwell characterizationwell 16awell 16b

Lightning Dock Geothermal Field GIS Data

Aug 19, 2026
1.34 GB
Curated
This submission houses geospatial data for the Lightning Dock geothermal (LDG) field in the Animas Valley, Hidalgo County, south-western New Mexico. LDG is a liquid-dominated system produced for binary (ORC) power generation. In this submission shp and tif files are zipped with al...
Authors
Ifrene, G. et al Zanskar Geothermal
geothermalenergygeospatiallightning dockgiswaterchemistrywell datageologicaltemperaturegeophysicalaeromagneticgravitylidarfaults

Utah FORGE 3-2535: Building a 3D Resistivity Model for Simulation and Survey Design of EM Measurements

Dec 01, 2022
3.23 MB
Publicly accessible
The included report outlines the creation of three 3D resistivity models that will be used to determine the sensitivity of EM measurements for the hypothetical stimulated reservoir at FORGE as well as for EM survey design. FORGE project 3-2535 is planning on using a casing source ...
Authors
Alumbaugh, D. et al Lawrence Berkeley National Laboratory
geothermalenergyutah forgeegsforgemodelingresistivity modelremote sensingwell characterizationwell 16awell 16b

Silver Peak Innovative Exploration Project (Ram Power Inc.)

Jan 01, 2010
463.6 MB
Publicly accessible
Data generated from the Silver Peak Innovative Exploration Project, in Esmeralda County, Nevada, encompasses a deep-circulation (amagmatic) meteoric-geothermal system circulating beneath basin-fill sediments locally blanketed with travertine in western Clayton Valley (lithium-rich...
Authors
Miller, C. Ram Power, Inc.
geothermalsilver peakgravitymagneticmtradiometricsregional temperatureremote sensingresource modelseismicfluid datawell dataphotosgeologywalker lanelate miocenepliocenelone mountainesmeralda countynevadagravity surveygridterrain5km10kmupward continued regional residualbougerhorizontal gravity gradientnorth americaimperial countymagnetic reporttmiigrftotal magentic intensitymagnetotelluric surveymt surveyresistivity3dground mtztemradiometric survey silver peak20102011temperatureshallow temperature gradienttemperature gradient holestghasterphotographs2dseismic reflection surveyfaultsmesquitefluidchemistrygeologymapgeospatial data
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