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Utah FORGE: Core Material Friction Experiments
The following folders contain 3 friction experiments on Utah FORGE core material from depths of 6735 8533ft. The experiment conditions range from 100% relative humidity at room temperature to fluid-saturated at 110C. Experiments were done on both intact samples in a single-direct ...
Marone, C. et al Pennsylvania State University
Mar 15, 2023
7 Resources
0 Stars
Curated
7 Resources
0 Stars
Curated
Geothermal Play-Fairway Analysis of Washington State Prospects: Final Report
This package includes the final technical report for the Play-Fairway project in Washington State. It includes all activities and reporting from phases 1, 2, and 3. The primary goal of this study is to develop a suite of tools and methods that help identify a ?fairway? where the t...
Steely, A. et al Washington Geological Survey
Sep 30, 2021
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Natural Reservoir Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin
The files included in this submission contain all data pertinent to the methods and results of this task's output, which is a cohesive multi-state map of all known potential geothermal reservoirs in our region, ranked by their potential favorability. Favorability is quantified usi...
Jordan, T. and Camp, E. Cornell University
Oct 22, 2015
9 Resources
0 Stars
Publicly accessible
9 Resources
0 Stars
Publicly accessible
Stanford Thermal Earth Model for the Conterminous United States
Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States....
Aljubran, M. and Horne, R. Stanford University
Mar 14, 2024
9 Resources
1 Stars
Curated
9 Resources
1 Stars
Curated
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
DEEPEN: Final 3D PFA Favorability Models and 2D Favorability Maps at Newberry Volcano
Part of the DEEPEN (DE-risking Exploration of geothermal Plays in magmatic ENvironments) project involved developing and testing a methodology for a 3D play fairway analysis (PFA) for multiple play types (conventional hydrothermal, superhot EGS, and supercritical). This was tested...
Taverna, N. et al National Renewable Energy Laboratory
Jan 24, 2024
14 Resources
0 Stars
Publicly accessible
14 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
6 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
Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)
This submission contains information used to compute the risk factors for the GPFA-AB project. The risk factors are natural reservoir quality, thermal resource quality, potential for induced seismicity, and utilization. The methods used to combine the risk factors included taking ...
E., T. Cornell University
Sep 30, 2015
191 Resources
0 Stars
Publicly accessible
191 Resources
0 Stars
Publicly accessible