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Utah FORGE: Phase 2C Seismic Observation and Ground Water Well Data and Well Locations
This submission contains the following data associated with Utah FORGE Phase 2C within the Roosevelt Hot Springs geothermal area:
An ArcGIS shapefile with well locations for wells 58-32, 78-32, 68-32, OH-3, OH-4, WOW-2, and WOW-3. Well 58-32 is the deep test well, wells 68-32 an...
Abraham, S. et al Energy and Geoscience Institute at the University of Utah
Mar 26, 2019
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Utah FORGE: Phase 2C Topical Report
This is the topical report that wraps up the work and results achieved during Utah FORGE Phase 2C. The zip file includes several folders containing (1) an overview; (2) the results; (3) the lessons learned; and (4) the conclusions. It also contains a folder containing appendices i...
Moore, J. et al Energy and Geoscience Institute at the University of Utah
Dec 11, 2019
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: Microseismic Monitoring
The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...
Schoenball, M. et al Lawrence Berkeley National Laboratory
Jul 29, 2019
46 Resources
0 Stars
Curated
46 Resources
0 Stars
Curated
Penn State Lab Testing Fluid-Rock Interaction in Geothermal Reservoirs
This project focused on assessment and discovery of fluid-rock interaction in geothermal reservoirs. We accomplished work in four main areas: 1) fracture formation and the relationship between fluid flow and shear failure, 2) assessment of fracture geometry and fluid permeability ...
Madara, B. et al Pennsylvania State University
Jan 01, 2018
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Newberry EGS Demonstration: Well 55-29 Stimulation Data
The Newberry Volcano EGS Demonstration in central Oregon, a 3 year project started in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ...
T., T. AltaRock Energy Inc
Dec 08, 2012
136 Resources
0 Stars
Curated
136 Resources
0 Stars
Curated
Hybrid machine learning model to predict 3D in-situ permeability evolution
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Newberry EGS Demonstration: Well 55-29 Stimulation Data 2014
The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ru...
Cladhouhos, T. et al AltaRock Energy Inc
Sep 03, 2015
54 Resources
0 Stars
Curated
54 Resources
0 Stars
Curated
Final Report: Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin
This is a final report summarizing a two-year (2014-16) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and ...
E. Jordan, T. Cornell University
Nov 18, 2015
12 Resources
0 Stars
Publicly accessible
12 Resources
0 Stars
Publicly accessible