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Using Fully Coupled Hydro-Geomechanical Numerical Test Bed to Study Reservoir Stimulation with Low Hydraulic Pressure
This paper documents our effort to use a fully coupled hydro-geomechanical numerical test bed to study using low hydraulic pressure to stimulate geothermal reservoirs with existing fracture network. In this low pressure stimulation strategy, fluid pressure is lower than the minimu...
Fu, P. et al Lawrence Livermore National Laboratory
Jan 31, 2012
2 Resources
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2 Resources
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Modeling Responses of Naturally Fractured Geothermal Reservoir to Low-Pressure Stimulation
Hydraulic shearing is an appealing reservoir stimulation strategy for Enhanced Geothermal Systems. It is believed that hydro-shearing is likely to simulate a fracture network that covers a relatively large volume of the reservoir whereas hydro-fracturing tends to create a small nu...
Fu, P. and Carrigan, C. Lawrence Livermore National Laboratory
Jan 01, 2012
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2 Resources
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Utah FORGE LBNL 3-2535 Preliminary Report on Development of a Reservoir Seismic Velocity Model
This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation.
A preliminary 3D velocity model for the larg...
Gritto, R. Array Information Technology
Jan 30, 2023
1 Resources
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1 Resources
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Utah FORGE Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study
This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model was developed using RMS velocities of the seismic reflection su...
Vasco, D. and Chan, C. Array Information Technology
Apr 30, 2022
2 Resources
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2 Resources
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Utah FORGE Project 2439: Machine Learning for Well 16A(78)-32 Stress Predictions
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...
Kelley, M. et al Battelle Memorial Institute
Jun 19, 2023
1 Resources
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1 Resources
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Full Moment Tensor Inversion Software
The link points to a website at NCEDC to download the full moment tensors inversion software The moment tensor analysis conducted in the current project is based on the full moment tensor model described in Minson and Dreger (2008). The software including source, examples and tut...
Gritto, R. and Dreger, D. Array Information Technology
Oct 31, 2018
1 Resources
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1 Resources
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WISE-CASING: Seismic Experiment at Richmond Field Station, CA
This experiment is testing the tube waves reflected from the bottom of the well. We put six single-channel geophones on the surface and a 24-channel downhole hydrophone into the well. The well is about 30 meters deep. Just a steel casing in the sand formation, no cement.
Wu, Y. et al Lawrence Berkeley National Laboratory
Apr 25, 2018
32 Resources
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32 Resources
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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
6 Resources
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6 Resources
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