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Exploration Best Practices on OpenEI
This is an electronic database detailing different types of, various phases of, best practices for, and cost and time associated with geothermal exploration techniques. The groups of exploration techniques included in the database are Data and Modeling Techniques, Downhole Techniq...
Young, K. National Renewable Energy Laboratory
Sep 20, 2013
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Brady Geothermal 1D Seismic Velocity Model
This submission contains an ASCII text file of seismic velocities derived from ambient noise cross-correlation used to create a model of seismic velocity as a 1-D function of depth in addition to a quarterly report describing the creation and use of the model. Model uses 28 Green'...
Matzel, E. Lawrence Livermore National Laboratory
Feb 17, 2015
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
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Utah FORGE 3-2535: Joint EM-Seismic-InSAR Imaging of Fracture Properties Workshop Presentation
This is a presentation on the Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development project by Lawrence Berkeley National Laboratory, presented by Dr. David Alumbaugh, Staff Sc...
Alumbaugh, D. Lawrence Berkeley National Laboratory
Sep 08, 2023
1 Resources
0 Stars
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1 Resources
0 Stars
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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
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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
12 Resources
0 Stars
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12 Resources
0 Stars
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GeoDAWN: Airborne magnetic and radiometric surveys of the northwestern Great Basin, Nevada and California
This submission encompasses the airborne magnetic and radiometric survey data from the northwestern Great Basin in Nevada and California, collected under the GeoDAWN initiative: Geoscience Data Acquisition for Western Nevada. Included in the dataset are all flight details, geophys...
Glen, J. and Earney, T. United States Geological Survey
Mar 01, 2024
4 Resources
0 Stars
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4 Resources
0 Stars
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Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data
Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...
Reinisch, E. University of Wisconsin
Jul 28, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
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Porotomo: InSAR Data from San Emidio Geothermal Field, Nevada, 1992-2010
This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering San Emidio Geothermal Field in Nevada, USA as part of the porotomo project. Data included within this submission are the following:
> ENVI_T120_GDR.tgz: Tarred direc...
Reinisch, E. and Feigl, K. University of Wisconsin
Jun 25, 2019
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
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