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EGS Collab Experiment 2: Earth Model Datasets
The EGS Collab Project performed a series of tests to increase the understanding the response of crystalline rock mass to stimulations and fluid circulation to efficiently implement enhanced geothermal systems (EGS) technologies. The EGS Collab team created two underground testbed...
Neupane, G. et al Idaho National Laboratory
May 29, 2022
6 Resources
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6 Resources
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Publicly accessible
Dynamic Earth Energy Storage: Terawatt-year, Grid-scale Energy Storage Using Planet Earth as a Thermal Battery (GeoTES): Phase I Project Final Report
Final report for the DOE GTO funded research on geologic thermal energy storage (GeoTES), or commonly known as reservoir thermal energy storage (RTES).
The results described in this report shed light on various aspects of RTES including project siting, operational performance, m...
Atkinson, T. et al Idaho National Laboratory
Sep 02, 2022
1 Resources
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1 Resources
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Dynamic Earth Energy Storage: Terawatt-Year, Grid-Scale Energy Storage using Planet Earth as a Thermal Battery (GeoTES): Seedling Project Final Report
Grid-scale energy storage has been identified as a needed technology to support the continued build-out of intermittent renewable energy resources. As of April 2017, the U.S. had approximately 24.2 GW of energy storage on line, compared to 1,081 GW of installed generation capacity...
McLing, T. et al Idaho National Laboratory
May 31, 2019
11 Resources
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11 Resources
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EGS Collab Experiment 1: Second Set Tracer Test Results
The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead,...
Neupane, G. et al Idaho National Laboratory
Dec 19, 2019
4 Resources
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4 Resources
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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
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4 Resources
0 Stars
Publicly accessible