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"triaxial direct shear"×
Conventional Hydrothermal×

Utah FORGE: Slide-Hold-Slide Experiments on Westerly Granite at Temperatures up to 250 Degrees C

Laboratory slide-hold-slide tests were conducted in a conventional triaxial deformation configuration on 1-inch diameter cylindrical cores of Westerly granite bisected by a sawcut oriented at 30 degrees from vertical. Tests were conducted at a constant confining pressure of 30 MPa...
Jeppson, T. et al United States Geological Survey
Oct 10, 2023
2 Resources
0 Stars
Publicly accessible

Performance, Cost, and Financial Parameters of Geothermal District Heating Systems for Market Penetration Modeling under Various Scenarios

The U.S. Department of Energy Geothermal Vision (GeoVision) Study is currently looking at the potential to increase geothermal deployment in the U.S. and to understand the impact of this increased deployment. This paper reviews 31 performance, cost, and financial parameters as inp...
Beckers, K. and Young, K. National Renewable Energy Laboratory
Mar 23, 2017
1 Resources
1 Stars
Publicly accessible

Utah FORGE 5-2565: Hydrothermal Evolution of Fracture Properties Workshop Presentation

This is a presentation on the Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions project by the U.S. Geological Survey, presented by Dr. David Lockner. The project's objective was to determine how thermal, hydraulic, mechanical, and ch...
Lockner, D. et al United States Geological Survey
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

Hawthorne Nevada Deep Direct-Use Feasibility Study Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicl...
Ayling, B. and Hinz, N. Great Basin Center for Geothermal Energy
Apr 05, 2020
7 Resources
0 Stars
Publicly accessible

PoroTomo: BRAD and BRDY GPS Station RINEX Files December 20, 2014

This dataset provides links to daily RINEX files for two GPS stations at Brady's Hot Springs as of December 20, 2014. The data is formatted as compressed GNSS RINEX observation files and is accessible through CSV files containing metadata such as file size, data type, and publicat...
Kreemer, C. University of Nevada
Dec 20, 2014
4 Resources
0 Stars
Publicly accessible

PoroTomo: BRAD and BRDY GPS Station RINEX Files March 26, 2015

This dataset provides links to daily RINEX files for two GPS stations at Brady's Hot Springs as of March 26, 2015. The data is formatted as compressed GNSS RINEX observation files, accessible through formatted CSV files, as well as in links to the complete daily time series data. ...
Kreemer, C. University of Wisconsin
Jan 01, 2015
7 Resources
0 Stars
Curated

PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data

This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
20 Resources
1 Stars
Publicly accessible

DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
4 Resources
1 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

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
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  • 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.

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