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EGS Collab: 3D Geophysical Model Around the Sanford Underground Research Facility
This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P and S-wave seismic speeds on a 3D grid. The file has six columns and provides latit...
Chai, C. et al Lawrence Berkeley National Laboratory
Feb 06, 2019
3 Resources
0 Stars
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3 Resources
0 Stars
Publicly accessible
Early Market Opportunity MHK Energy Site Identification Wave and Tidal Resources
This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--base...
Kilcher, L. National Renewable Energy Laboratory
Apr 01, 2016
7 Resources
0 Stars
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7 Resources
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Catalyst Design in Nitrate Removal
Based on the volcano plot developed by Dr. Goldsmith group (Report linked in submission), we utilized DFT (density functional theory) calculations to search for bimetallic materials in the application of catalysts in aqueous nitrate removal. The calculations are conducted via the ...
Wang, D. and Jain, A. Lawrence Berkeley National Laboratory
Dec 01, 2021
7 Resources
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7 Resources
0 Stars
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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification.
In this study, a machine-learning-assiste...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
0 Stars
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4 Resources
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Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests: Hydraulic Data
Hydraulic responses from periodic hydraulic tests conducted at the Mirror Lake Fractured Rock Research Site, during the summer of 2015. These hydraulic responses were measured also using distributed acoustic sensing (DAS) which is cataloged in a different submission under this gr...
Cole, M. California State University
Jul 31, 2015
6 Resources
0 Stars
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6 Resources
0 Stars
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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
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6 Resources
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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
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6 Resources
0 Stars
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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
45 Resources
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45 Resources
0 Stars
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