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Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2024 Annual Workshop Presentation

This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate...

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

Sep 17, 2024
1 Resources
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Utah FORGE 3-2417: Simulations for Distributed Acoustic Sensing Strain Signatures as an Indicator of Fracture Connectivity

This dataset encompasses simulations of strain signatures from both hydraulically connected and "near-miss" fractures in enhanced geothermal systems (EGS). The files and results are presented from the perspective of digital acoustic sensing's (DAS) potential to differentiate the t...

Ward-Baranyay, M. et al Rice University

Jan 01, 2023
4 Resources
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MT Data: Newberry 4D Monitoring EGS Project

This submission contains a link to the EDX Collaborative Workspace where the MT data collected in support of the DOE GTO 4D EGS monitoring project is stored. Daily production reports- Oregon State University (OSU) had 6 stations running continuously. --Dynamic survey map, KML f...

Rose, K. National Energy Technology Laboratory

Apr 12, 2016
1 Resources
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Publicly accessible

Utah FORGE: Fiber Optic Cumulative Strain Change and Strain Change Rate Data From Well 16A Stimulation at Well 16B

This dataset includes Rayleigh Frequency Shift (RFS) Distributed Strain Sensing (DSS) cumulative strain change and change rate data. The data was acquired during the stimulation of Utah FORGE Well 16A(78)-32 in April 2024 via fiber installed in Well 16B(78)-32. The fiber optic da...

Khatara, S. et al Neubrex Energy Services (US), LLC

Nov 06, 2024
2 Resources
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Using Fully Coupled Hydro-Geomechanical Numerical Test Bed to Study Reservoir Stimulation with Low Hydraulic Pressure

This paper documents our effort to use a fully coupled hydro-geomechanical numerical test bed to study using low hydraulic pressure to stimulate geothermal reservoirs with existing fracture network. In this low pressure stimulation strategy, fluid pressure is lower than the minimu...

Fu, P. et al Lawrence Livermore National Laboratory

Jan 31, 2012
2 Resources
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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
1 Resources
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EGS Collab Experiment 1: Continuous Active-Source Seismic Monitoring (CASSM) Data

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. and Sprinkle, P. Lawrence Berkeley National Laboratory

Apr 25, 2018
6 Resources
1 Stars
Publicly accessible

Utah FORGE: Phase 1a Tensor Strainmeter Data for the April, 2022 Stimulation of Well 16A(78)-32

Data from two Tensor Optical Fiber Strainmeters that were operational during Stages 1, 2, and 3 of the April, 2022 stimulation of well 16A(78)-32. Each csv file contains data from each stimulation stage (stage1, stage2, stage3) for both Phase 1a strainmeter installations (FS01, f...

DeWolf, S. and Murdoch, L. Clemson University

Sep 15, 2022
8 Resources
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Investigation of Stimulation-Response Relationships for Complex Fracture Systems in Enhanced Geothermal Reservoirs

Hydraulic fracturing is currently the primary method for stimulating low-permeability geothermal reservoirs and creating Enhanced (or Engineered) Geothermal Systems (EGS) with improved permeability and heat production efficiency. Complex natural fracture systems usually exist in ...

Fu, P. et al Lawrence Livermore National Laboratory

Jan 01, 2011
2 Resources
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Utah FORGE: Well 16A(78)-32 Stimulation Data (April, 2022)

This is a set of data related to the stimulation program at Utah FORGE well 16A(78)-32 during April, 2022. This includes daily reports, 1 second Pason data, tracer data, and shear stimulation data and information including a report of an evolving prognosis for the stimulation oper...

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

May 18, 2022
11 Resources
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Utah FORGE 1-2551: Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores Workshop Presentation and Report

Included here are a presentation recording, slides, and report on the Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores project by Colorado School of Mines, presented by Dr. William W. Fleckenstei...

Fleckenstein, W. et al Colorado School of Mines

Sep 08, 2023
3 Resources
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EGS Collab Experiment 1: Earth Model Input Files

The EGS Collab is conducting experiments in hydraulic fracturing at a depth of 1.5 km in the Sanford Underground Research Facility (SURF) on the 4850 Level. A total of eight ~60m-long subhorizontal boreholes were drilled at that depth on the western rib of the West Access Drift. S...

Neupane, G. and Sigma-V, T. Idaho National Laboratory

Dec 19, 2019
6 Resources
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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
2 Resources
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EGS Collab Experiment 1: Microseismic Monitoring

Schoenball, M. et al Lawrence Berkeley National Laboratory

Jul 29, 2019
46 Resources
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