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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
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Utah FORGE: Laboratory Experiments Examining the Effect of Thermal and Mechanical Processes on Hydraulic Transmissivity Evolution

Using laboratory slide-hold-slide experiments, at temperatures from 22 to 200 degrees C, to examine effects of fracture reactivation and quasi-static loading on the evolution of fluid transport properties of simulated fractures in Westerly granite. At all temperatures, the in-plan...

Lockner, D. et al United States Geological Survey

Apr 03, 2023
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Curated

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
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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
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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
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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
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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
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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
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