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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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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
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Reactive Transport Simulations of High-Tempertature Geologic Thermal Energy Storage (GeoTES) in Deep Saline Formations I/O Files

Simulation input and output files, post-processed figures and excel tables, and tecplot layout files for generating figures. These simulations were run with TOUGHREACT V4.12 by Lawrence Berkeley National Laboratory in 2021. This work was completed as part of the geologic thermal e...
Spycher, N. and Doughty, C. Lawrence Berkeley National Laboratory
Dec 31, 2021
2 Resources
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SMP and Fracture Modeling

The problem of loss circulation in geothermal wells is inherently challenging due to high temperatures, brittle rocks, and presence of abundant fractures. Because of the inherent challenges in geothermal environments, there are limitations in selecting proper lost circulation mate...
Salehi, S. et al University of Oklahoma
Oct 01, 2021
4 Resources
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