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 - 4 of 4.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"stage 8"×
Well Logging and Testing×

Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

Aug 30, 2024
973.4 kB
Publicly accessible
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Authors
Lu, G. et al University of Pittsburgh
geothermalenergyutah forgein-situ stress estimationphysics-based modelingfinite element methodmachine learning modelthermo-poro-mechanical effectwell loggingvelocity-to-stress relationshipmachine learningfemreporttechnical report16a78-32mlegs2-2439v2principal stressstress predictionfar-fieldpre-cooling

Fallon FORGE: Lithology Logs and Well 21-31 Drilling Data

Mar 11, 2018
128.85 MB
Publicly accessible
This submission includes lithology logs for all Fallon FORGE area wells; determined from core, cuttings, and thin section. Wells included are 84-31, 21-31, 82-36, FOH-3D, 62-36, 18-5, 88-24, 86-25, FOH-2, 14-36, 17-16, 34-33, 35A-11, 51A-20, 62-15, 72-7, 86-15, Carson_Strat_1_36-3...
Authors
Blankenship, D. et al Sandia National Laboratories
geothermalenergyfallonforgeegsnevadalithologywellscorecuttingsdepth intervalsgeologyvetted-nodrill logwell loggeologic unitextentnvdrillingloggingmud reportdrilling parametersmud lossesdirectional drillingwireline logsfracturesmineralsmineralogytemperaturegasesgamma raygamma radiationself potentialspontaneous potentialresistivitynphole diametersphi21-31datawelllog

Utah FORGE: Well 16A(78)-32 Logs

Mar 08, 2021
10.01 GB
Publicly accessible
This dataset contains all well logs from Utah FORGE well 16A(78)-32. This includes the mud log, Sanvean Technologies logs, and Schlumberger logs. Please see the file descriptions below for information about each log.
Authors
Gilmour, B. et al Energy and Geoscience Institute at the University of Utah
geothermalenergywell 16a78-32 drilling logsutah forgeforgewell 16a78-32 sanvean logswell 16a78-32 schlumberger logswell 16a78-32 mud logutah geothermalwell dataloggingmud logsanvean logsschlumberger logs16a78-32well logegssanveanschlumbergerlithologyfmiformation microimagerfullborewellborecorecharacterizationdrillgeologydrill ratemineralstemperaturerate of penetrationropdrill stem test

Utah FORGE 2439: Well 16B(78)-32 Field-Test Data from Mini-Frac Tests

Jul 02, 2023
2.73 GB
Publicly accessible
This submittal includes the field-test data collected during stress tests conducted in the Utah FORGE 16B(78)-32 wellbore to measure/characterize the stresses in the geothermal reservoir. The type of stress test performed is referred to as a mini-frac test or a micro-frac test. Th...
Authors
Kelley, M. et al Battelle Memorial Institute
geothermalenergygeomechanicsutahforgeminifracstressin-situ stressegsmini-fracstress testgeophysical logimage logacoustic logsonic logfracturinghydraulic fracturingreservoir stressinjectioncaliper logstemperature logsxmac16b78-32baker hughespacker element pressureflowbackpacker element
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