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DEMO-FTES Test 1: Water Flow, Pressure, Temperature, and Electrical Conductivity Data

This dataset contains 1-second and hourly resolution water flow rate, pressure, temperature, and electrical conductivity data collected during Test 1 of the DEMO Fracture Thermal Energy Storage (FTES) project at the Sanford Underground Research Facility (SURF) between December 10,...
Burghardt, J. et al Pacific Northwest National Laboratory
Apr 16, 2025
4 Resources
0 Stars
Curated

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
2 Resources
0 Stars
Publicly accessible

Alternative CAES Technology Using Depleted Unconventional Gas Wells and Subsurface Thermal Energy Storage (GeoCAES)

This project assessed the technical viability of a process called GeoCAES. The process stores electrical energy by injecting natural gas into shale gas formations using a compressor, storing it, and producing it through an expander to generate electricity. This data submission inc...
Johnston, H. and Young, D. National Renewable Energy Laboratory
May 23, 2019
8 Resources
1 Stars
Publicly accessible

Elevation Grid for top Columbia River Basalt (CRBG) in the Portland Basin used in DDU Feasibility Study

The Portland Basin is a prime location to assess the feasibility of DDU-TES because natural geologic conditions provide thermal and hydraulic separation from overlying aquifers that would otherwise sweep away stored heat. Under the Portland Basin, the lower Columbia River Basalt G...
Bershaw, J. and Scanlon, D. Portland State University
Dec 01, 2018
5 Resources
0 Stars
Publicly accessible

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
Publicly accessible
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  • The GDR is the submission point for all data collected from research funded by the U.S. Department of Energy's Geothermal Technologies Office.
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