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EGS Collab Experiment 2: Microseismic Monitoring

This dataset contains continuous seismic waveform data recorded during stimulation and thermal circulation tests for the Enhanced Geothermal Systems (EGS) Collab Experiment #2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Da...

Hopp, C. Lawrence Berkeley National Laboratory

May 28, 2024
4 Resources
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Curated

Utah FORGE: Well 58-32 Stimulation Conference Paper and Data

The U.S. Department of Energy's (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in ...

Best, S. Energy and Geoscience Institute at the University of Utah

Apr 24, 2019
2 Resources
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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
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Publicly accessible

Seismic Analysis of Spatio-Temporal Fracture Generation During EGS Resource Development Deviatoric MT, Fracture Network, and Final Report

This submission contains 167 deviatoric moment tensor (MT) solutions for the seismicity observed two years prior and three years post start of injection activities at The Geysers Prati 32 EGS Demonstration. Also included is a statistical representation of the properties of 751 fra...

Gritto, R. et al Array Information Technology

Sep 01, 2018
3 Resources
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Publicly accessible

Utah FORGE: Final Topical Report 2018

This is the final topical report for the Phase 2B Utah FORGE project, which is located near Roosevelt Hot Springs, Utah. This PDF format report details results associated with the conceptual geologic model, deep well 58-32, rock geomechanics, reservoir temperatures, seismic survey...

Moore, J. et al Energy and Geoscience Institute at the University of Utah

Apr 07, 2018
2 Resources
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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
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