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Utah FORGE 5-2615: Well 58-32 and 78-32 Poroelastic Properties

Lab data on permeability, grain bulk modulus, drained bulk modulus, Skempton's pore pressure coefficient, and Biot's effective stress coefficient for Utah Forge Well 58-32 and Well 78-32. Work done as part of project number 5-2615 by the University of Oklahoma.

Ghassemi, A. and Zhou, X. University of Oklahoma

Oct 31, 2022
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West Flank Coso FORGE: Geologic Cross-Sections

Geologic cross sections from the West Flank FORGE site. Cross Section traces linked in resources.

Blankenship, D. Sandia National Laboratories

Mar 01, 2016
2 Resources
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Exploration Gap Assessment (FY13 Update)

This submission contains an update to the previous Exploration Gap Assessment funded in 2012, which identify high potential hydrothermal areas where critical data are needed (gap analysis on exploration data). The uploaded data are contained in two data files for each data catego...

Esposito, A. et al National Renewable Energy Laboratory

Sep 30, 2013
36 Resources
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Fallon FORGE: Analogue Outcrop Samples

Compilation of results for mechanical and fluid flow properties of analogue outcrop samples experimental data for compressional and shear wave velocities, tensile strengths, and compressive strengths. Outcrop location and sample orientation data are documented in a separate csv file.

Blankenship, D. et al Sandia National Laboratories

Mar 12, 2018
2 Resources
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Snake River Plain FORGE: Well Data for USGS-142

Well data for the USGS-142 well located in eastern Snake River Plain, Idaho. This data collection includes lithology reports, borehole logs, and photos of rhyolite core samples. This collection of data has been assembled as part of the site characterization data used to develop ...

Twining, B. Idaho National Laboratory

Nov 23, 2015
6 Resources
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Fallon FORGE: Lithology Logs and Well 21-31 Drilling Data

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...

Blankenship, D. et al Sandia National Laboratories

Mar 11, 2018
2 Resources
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Snake River Plain FORGE: Well Data for INEL-1

Well data for the INEL-1 well located in eastern Snake River Plain, Idaho. This data collection includes caliper logs, lithology reports, borehole logs, temperature at depth data, neutron density and gamma data, full color logs, fracture analysis, photos, and rock strength paramet...

Prestwich, S. and Bowman, J. Idaho National Laboratory

Mar 01, 1979
34 Resources
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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021

This submission contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in ...

Kleich, S. et al University of Wisconsin Madison

Jan 12, 2021
5 Resources
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Snake River Plain FORGE: Site Characterization Data

The site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. This collection includes data on seismic events, groundwater,...

Moos, D. and Barton, C. Idaho National Laboratory

Apr 18, 2016
49 Resources
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3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

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...

Siler, D. and Pepin, J. United States Geological Survey

Oct 01, 2021
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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
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