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Alternative Geothermal Power Production Scenarios

The information given in this file pertains to Argonne life-cycle analyses (LCAs) of the plant cycle stage for a set of ten new geothermal scenario pairs, each comprised of a reference and improved case. These analyses were conducted to compare environmental performances among the...

Sullivan, J. Argonne National Laboratory

Mar 14, 2014
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USGS Geophysics, Heat Flow, and Slip and Dilation Tendency Data used in Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geoph...

DeAngelo, J. et al Nevada Bureau of Mines and Geology

Jun 01, 2021
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DEEPEN 3D PFA Index Models for Exploration Datasets at Newberry Volcano

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), index models needed to be de...

Taverna, N. et al National Renewable Energy Laboratory

Jun 30, 2023
6 Resources
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Play Fairway Analysis of the Snake River Plain, Idaho: Final Report

This submission includes the final project report of the Snake River Plain Play Fairway Analysis project as well as a separate appendix for the final report. The final report outlines the application of Play Fairway Analysis (PFA) to geothermal exploration, specifically within the...

Shervais, J. et al Utah State University

Feb 19, 2021
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GIS Resource Compilation Map Package Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

This submission contains an ESRI map package (.mpk) with an embedded geodatabase for GIS resources used or derived in the Nevada Machine Learning project, meant to accompany the final report. The package includes layer descriptions, layer grouping, and symbology. Layer groups incl...

Brown, S. et al Nevada Bureau of Mines and Geology

Jun 01, 2021
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Passive Seismic Emission Tomography Results at San Emidio Nevada

The utility of passive seismic emission tomography for mapping geothermal permeability has been tested at San Emidio in Nevada. The San Emidio study area overlaps a geothermal field in production since 1987 and another resource to the south of the production field. Passive seismic...

Warren, I. et al Ormat Technologies, Inc.

Dec 01, 2016
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SSGF Mineral Major Elements and Lithium Concentration

Presented are major element and lithium concentrations of minerals from the Salton Sea Geothermal Field (SSGF), located in the Imperial Valley, California. With a recent increase in demand for lithium, the area is now being studied as a source of geothermal brine for lithium extr...

Humphreys, J. et al Lawrence Berkeley National Laboratory

May 01, 2023
8 Resources
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Curated

Renewable Energy Potential Model: Geothermal Supply Curves

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmenta...

Trainor-Guitton, W. et al National Renewable Energy Laboratory

Aug 21, 2023
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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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Appendices for Geothermal Exploration Artificial Intelligence Report

The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...

Duzgun, H. et al Colorado School of Mines

Jan 08, 2021
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