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Utah FORGE: Seismic Activity from April, 2019

This dataset contains seismic event detections acquired using the 151 Nodal geophones deployed at the Utah FORGE site in April 2019. Details regarding the publishing are available in the paper linked below (Mesimeri, M. and K. L. Pankow et al. 2020). A frequency-domain-based algor...

Pankow, K. University of Utah Seismograph Stations

May 01, 2019
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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 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
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Utah FORGE: Induced Seismicity Mitigation Plan

This is the current induced seismicity mitigation plan (ISMP) for the Utah FORGE project. Information that was collected during Phases 1 and 2 of the Utah FORGE project has been incorporated, as have literature searches and risk assessments. The purpose of this report is to identi...

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

Dec 30, 2020
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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
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Final Report: Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

This is a final report summarizing a two-year (2014-16) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and ...

E. Jordan, T. Cornell University

Nov 18, 2015
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Appalachian Basin Play Fairway Analysis Gravity, Magnetics, and Earthquake Data

This archived dataset contains magnetic and gravity imaging data for the Appalachian Basin, compiled using Poisson Wavelet Multiscale Edge Detection, referred to as 'worm' for brevity, and stored in a PostGIS database, along with shapefiles and CSVs of relevant data. The archive ...

Horowitz, F. Cornell University

Jul 20, 2016
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University of Illinois Campus Deep Direct-Use Feasibility Study Design of Injection Well #1 (CCS1)

Includes specification sheet, wellbore geometry, and drilling fluids at section target depth associated with the design of Injection Well #1 (CCS1) for the Illinois Basin Decatur Project (IBDP).

Greenberg, S. University of Illinois

Mar 30, 2018
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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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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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