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Utah FORGE: Phase 2C Seismic Observation and Ground Water Well Data and Well Locations

This submission contains the following data associated with Utah FORGE Phase 2C within the Roosevelt Hot Springs geothermal area: An ArcGIS shapefile with well locations for wells 58-32, 78-32, 68-32, OH-3, OH-4, WOW-2, and WOW-3. Well 58-32 is the deep test well, wells 68-32 an...

Abraham, S. et al Energy and Geoscience Institute at the University of Utah

Mar 26, 2019
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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
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Seismic Analysis of Spatio-Temporal Fracture Generation During EGS Resource Development Full Moment Tensors and Stress Inversion Catalogs

This submission contains 167 full moment tensor (MT) solutions for the seismicity observed two years prior and three years post start of injection activities. Also included are the azimuth and plunge angles for the three main stress directions sigma1, sigma 2 and sigma 3 at the P...

Gritto, R. et al Array Information Technology

Sep 26, 2018
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Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...

Zhu, T. Pennsylvania State University

May 05, 2021
4 Resources
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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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Utah FORGE: Microseismic Events

This archive contains Excel spreadsheets containing microseismic events detected in the study area during Utah FORGE Phase 2C. The Readme file included that describes the meaning of the abbreviations used as field headers in the spreadsheets. Additionally, there is a .dat (text) f...

Rutledge, J. Energy and Geoscience Institute at the University of Utah

Jul 08, 2019
2 Resources
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Utah FORGE: Earthquake Catalog

This is the set of earthquake catalogs developed for the Utah FORGE project covering December of 2016 through March of 2018. These are discussed in the "Utah FORGE Phase 2B Final Topical Report," which can be found on GDR under id: 1038 (See link 'Final Topical Report' in resource...

Pankow, K. Energy and Geoscience Institute at the University of Utah

Mar 21, 2018
2 Resources
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GEISER Project The Geysers Seismic Broadband Data 2012 2013

This link points to the Northern California Earthquake Data Center (NCEDC) to access The Geysers seismic broadband data. The two available data sets consist of continuous waveform data recorded at The Geysers from July 2012 to July 2013 and a processed catalog with earthquake info...

Gritto, R. Array Information Technology

Oct 31, 2018
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Utah FORGE: High-Resolution DAS Microseismic Data from Well 78-32

This regards a high-resolution DAS microseismic dataset produced by Silixa from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. It is a very large dataset and as such it is currently not directly available on GDR. However, it is availabl...

Martin, T. and Nash, G. Energy and Geoscience Institute at the University of Utah

Oct 20, 2019
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Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All expe...

Yu, J. et al Pennsylvania State University

Jul 01, 2023
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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
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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
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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
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EGS Collab Experiment 1: Microseismic Monitoring

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...

Schoenball, M. et al Lawrence Berkeley National Laboratory

Jul 29, 2019
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