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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
1 Resources
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1 Resources
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SMP Preparation, Programming, and Characterization
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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4 Resources
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Deep Sedimentary Basin EGS Development
Stratigraphic reservoirs with high permeability and temperature at economically accessible depths are attractive for power generation because of their large areal extent (> 100 km2) compared to the fault controlled hydrothermal reservoirs (< 10 km2) found throughout much of the we...
Allis, R. and Moore, J. University of Utah
Jan 24, 2013
1 Resources
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1 Resources
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Reservoir Stimulation Optimization with Operational Monitoring for Creation of EGS
EGS field projects have not sustained production at rates greater than half of what is needed for economic viability. The primary limitation that makes commercial EGS infeasible is our current inability to cost-effectively create high-permeability reservoirs from impermeable, igne...
A., C. Pacific Northwest National Laboratory
Sep 25, 2013
19 Resources
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19 Resources
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INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements
The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...
Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)
May 04, 2021
8 Resources
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8 Resources
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Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Fine Scale Stress Test Modelling
Mesh, properties, initial conditions, injection/withdrawal rates for modelling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, fo...
Smith, J. et al Lawrence Berkeley National Laboratory
Feb 22, 2021
14 Resources
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14 Resources
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Thermal-Hydrological-Mechanical Modelling of Stockton University Reservoir Cooling System, Large Scale Grid
Mesh, properties, initial conditions, injection/withdrawal rates for modeling thermal, hydrological, and mechanical effects of fluid injection to and withdrawal from ground for Stockton University reservoir cooling system (aquifer storage cooling system), Galloway, New Jersey, on ...
Smith, J. et al Lawrence Berkeley National Laboratory
Feb 26, 2021
15 Resources
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15 Resources
0 Stars
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