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Geothermal Energy×

Community Geothermal: Borefield Design, Thermal Conductivity, and Subsurface Modeling Data Chicago, IL

This dataset encompasses the development of a geothermal energy system for the West Woodlawn neighborhood in Chicago, Illinois. This project is part of a broader initiative to design and deploy geothermal heating and cooling systems at a community scale. The dataset includes therm...
Baser, T. et al Saint Louis University
Dec 04, 2023
6 Resources
0 Stars
Publicly accessible

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
0 Stars
Publicly accessible

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
0 Stars
Publicly accessible

University of Illinois Campus Deep Direct-Use Feasibility Study Thermal Properties of Geologic Formations in Illinois Basin

Thermal property data for rocks and and minerals and unconsolidated (glacial) sediments units from within and outside the Illinois Basin were compiled for modeling heat transport in the subsurface.
Lin, Y. et al University of Illinois
Mar 30, 2018
6 Resources
0 Stars
Publicly accessible

WISE-CASING: DC Simulation at Containment and Monitoring Institute (CaMI), Calgary, Canada

For the model calculation we applied EM3D using completion diagram of CaMI site and a background resistivity consistent with the borehole logs. It was also important to use the accurate position of the return electrode. We note that for the data fit the code also incorporated we...
Wang, J. and Wilt, M. Lawrence Berkeley National Laboratory
Apr 30, 2019
7 Resources
0 Stars
Publicly accessible

WISE-CASING: Frequency Domain EM Data from Cymric Oil Field, CA

Cymric oil field frequency domain electromagnetic (FEM) data with two parts of data labeled Part 1 and Part 2. Part 1 utilizes an electrical source line parallel to the receiver line, while Part 2 utilizes an electrical source line at a 75 deg angle to the receiver line. Data are ...
Wang, J. et al Lawrence Berkeley National Laboratory
Apr 30, 2019
11 Resources
0 Stars
Publicly accessible

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
0 Stars
Publicly accessible

EGS Collab: Modeling and Simulation Working Group Teleconference Series (99-128)

This submission contains the presentation slides and recordings from EGS Collab Modeling and Simulation Working Group (MSWG) teleconferences number 99 through 128. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field acti...
White, M. et al Pacific Northwest National Laboratory
Jun 07, 2022
31 Resources
0 Stars
Publicly accessible
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