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Utah FORGE: 2023 Induced Seismicity Mitigation Plan
This is the updated Utah FORGE Phase 3B induced seismicity mitigation plan (ISMP) covering the general Utah FORGE area. This new version incorporates newly collected seismic data, including data collected during the 2022 stimulation and a probabilistic seismic hazard assessment (...
Pankow, K. et al University of Utah Seismograph Stations
Aug 09, 2023
1 Resources
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1 Resources
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EGS Collab Experiment 1: Accelerometer orientations
Document describing the methodology used to determine the accelerometers' three-component orientations at the first EGS Collab testbed using Continuous Active-Source Seismic Monitoring (CASSM) data and hodogram analysis.
Original submission: gdr.openei.org/submissions/1166
Hopp, C. et al Lawrence Berkeley National Laboratory
Aug 19, 2020
2 Resources
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2 Resources
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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
6 Resources
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6 Resources
0 Stars
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Utah FORGE: Microseismic Event Catalogues from the Well 16A(78)-32 Stimulation in April, 2022
This dataset includes three microseismic event catalogues from the three stages of stimulation in April 2022 of well 16A(78)-32 derived by Geo Energie Suisse. Each spreadsheet contains source times, xy location, depth, and seismic moment magnitude. An animation of the order in whi...
Karvounis, D. et al University of Utah Seismograph Stations
Oct 10, 2023
2 Resources
0 Stars
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2 Resources
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Utah FORGE: Microseismic Monitoring Geophone Data from Well 78-32
This submission includes geophone data collected by Schlumberger from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. The data are hosted by the Center for High Performance Computing (CHPC) at the University of Utah, and a script for dow...
Pankow, K. University of Utah
Mar 18, 2020
5 Resources
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5 Resources
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Utah FORGE: Seismicity Associated with the 2019 Well 58-32 Stimulation
This catalog describes the seismicity associated with the 2019 stimulation at Utah FORGE. Containing both matched-filter detections (Dzubay et al., 2022) and Schlumberger-recorded events (detected with a 12-level geophone string), the final combined catalog contains a total of 534...
Pankow, K. University of Utah Seismograph Stations
Apr 30, 2019
1 Resources
1 Stars
Curated
1 Resources
1 Stars
Curated
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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3 Resources
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STRESSINVERSE Software for Stress Inversion
The STRESSINVERSE code uses an iterative method to find the nodal planes most consistent with the stress field given fault frictional properties. STRESINVERSE inverts the strike, rake and dip from moment tensor solutions for the in-situ state of stress. The code iteratively solves...
Gritto, R. Array Information Technology
Oct 31, 2018
1 Resources
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Publicly accessible
1 Resources
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Publicly accessible
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
2 Resources
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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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3 Resources
0 Stars
Publicly accessible