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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
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4 Resources
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Dataset and SUTRA model used to evaluate Reservoirs for Thermal Energy Storage in the Portland Basin, Oregon.
This is a link to the open access, published dataset and modeling that supports a feasibility study of Reservoir Thermal Energy Storage (RTES) in the Portland Basin, Oregon, USA.
Citation:
Burns, E.R., 2020, SUTRA model used to evaluate Saline or Brackish Aquifers as Reservoirs f...
Bershaw, J. et al Portland State University
Jun 29, 2020
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2 Resources
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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
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