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Validation of Innovative Exploration Technologies for Newberry Volcano: Raw Gravity Data
Validation of Innovative Exploration Technologies for Newberry Volcano: Raw data used to prepare the Gravity Report by Zonge 2012
Jaffe, T. Davenport Newberry Holdings, LLC
Oct 11, 2010
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Validation of Innovative Exploration Technologies for Newberry Volcano: Gravity Report
Report detailing data acquisition, quality, processing, and presentation for the gravity survey conducted on the Newberry Volcano.
(Validation of Innovative Exploration Technologies for Newberry Volcano: Gravity Report of Newberry prepared by Zonge GeoSciences 2012)
Jaffe, T. Davenport Newberry Holdings, LLC
Jan 06, 2012
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Appalachian Basin Play Fairway Analysis: Thermal Quality Analysis in Low-Temperature Geothermal Play Fairway Analysis (GPFA-AB)
This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylva...
E., T. Cornell University
Nov 15, 2015
50 Resources
0 Stars
Publicly accessible
50 Resources
0 Stars
Publicly accessible
Appalachian Basin Play Fairway Analysis Thermal Risk Factor and Quality Analyses
*This submission revises the analysis and products for Thermal Quality Analysis for the northern half of the Appalachian Basin (https://gdr.openei.org/submissions/638)*
This submission is one of five major parts of a Low Temperature Geothermal Play Fairway Analysis. Phase 1 of the...
Jordan, T. Cornell University
Aug 02, 2016
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Coupling Subsurface and Above-Surface Models for Optimizing the Design of Borefields and District Heating and Cooling Systems
Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduct...
Hu, J. et al Lawrence Berkeley National Laboratory
Jan 31, 2022
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible
Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Lu, G. et al University of Pittsburgh
Aug 30, 2024
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated