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"physics guided neural networks"×
Microseismicity×

Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events

This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
Williams, J. et al Global Technology Connection, Inc.
Jan 21, 2025
3 Resources
0 Stars
Publicly accessible

Microearthquake Studies at the Salton Sea Geothermal Field

The objective of this project is to detect and locate microearthquakes to aid in the characterization of reservoir fracture networks. Accurate identification and mapping of the large numbers of microearthquakes induced in EGS is one technique that provides diagnostic information w...
Templeton, D. Lawrence Livermore National Laboratory
Oct 01, 2013
1 Resources
1 Stars
Publicly accessible

Improved Microseismicity Detection During Newberry EGS Stimulations

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are oft...
Templeton, D. Lawrence Livermore National Laboratory
Oct 01, 2013
1 Resources
0 Stars
Publicly accessible

Improved Microseismicity Detection During Newberry EGS Stimulations

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are oft...
Templeton, D. Lawrence Livermore National Laboratory
Nov 01, 2013
1 Resources
0 Stars
Publicly accessible

Mapping Fracture Network Creation with Microseismicity During EGS Demonstrations

This a report for the project "Mapping Fracture Network Creation with Microseismicity During EGS Demonstrations". Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key too...
Templeton, D. et al Lawrence Livermore National Laboratory
Apr 18, 2014
1 Resources
0 Stars
Publicly accessible

Utah FORGE: 2024 Annual Report on Activities and Advancements

This 2024 annual report for Phase 3B Year 2 at Utah FORGE provides an in-depth account of activities and advancements made at the site. Key achievements include drilling and stimulating the production well 16B(78)-32, creating a geothermal reservoir, and achieving commercial-scale...
McLennan, J. et al Energy and Geoscience Institute at the University of Utah
Jan 27, 2025
1 Resources
1 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

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Chai, C. et al Oak Ridge National Laboratory
Apr 20, 2020
7 Resources
0 Stars
Publicly accessible

Hybrid machine learning model to predict 3D in-situ permeability evolution

Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 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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