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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
0 Stars
Curated
8 Resources
0 Stars
Curated
Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016
This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA.
Explanation of pair subdirectories:
Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011).
...
Reinisch, E. and Feigl, K. University of Wisconsin
Jun 25, 2019
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
DEEPEN 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments.
Part of the DEEPEN project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
27 Resources
0 Stars
Publicly accessible
27 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
6 Resources
0 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
6 Resources
0 Stars
Publicly accessible