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Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
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3 Resources
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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments
Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
Mordensky, S. et al United States Geological Survey
Feb 07, 2023
7 Resources
0 Stars
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7 Resources
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Utah FORGE 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model
This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation.
A preliminary 3D velocity model for the larg...
Gritto, R. Array Information Technology
Jan 30, 2023
1 Resources
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1 Resources
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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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1 Resources
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Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
0 Stars
Publicly accessible
12 Resources
0 Stars
Publicly accessible
Brady's Geothermal Field Seismic Network Metadata
Brady's geothermal field seismic network station locations and dates of operation.
Foxall, W. University of Wisconsin
Dec 21, 2014
1 Resources
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Publicly accessible
1 Resources
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Publicly accessible
Instructions for Downloading Brady Seismic Network Raw Waveform Data from NCEDC
Links and instructions for downloading Brady's triggered seismic network waveform data from the Northern California Earthquake Data Center (NCEDC). Data from 7/5/10-1/18/13 presently available.
Foxall, W. University of Wisconsin
Mar 31, 2015
1 Resources
0 Stars
Publicly accessible
1 Resources
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Publicly accessible
EGS Collab Experiment 2: Continuous Broadband Seismic Waveform Data
Two broadband seismometers were installed on the 4100 level and recorded for the duration of EGS Collab Experiment #2. Inspired by published data from similar instruments installed in the Aspo Hard Rock Lab, these long-period instruments aimed to measure the tilting of the drift i...
Rodriguez Tribaldos, V. Lawrence Berkeley National Laboratory
Sep 12, 2022
6 Resources
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Publicly accessible
6 Resources
0 Stars
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
1 Resources
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Utah FORGE: Well 16A(78)-32 Simplified Discrete Fracture Network Data
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
Finnila, A. Golder Associates Inc.
Jun 01, 2021
3 Resources
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3 Resources
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EGS Collab Experiment 1: Common Discrete Fracture Network
This package includes data and models that support hydraulic fracture stimulation and fluid circulation experiments in the Sanford Underground Research Facility (SURF). A paper by Schwering et al. (2020) describes the deterministic basis for developing a "common" discrete fracture...
Schwering, P. et al Sandia National Laboratories
Sep 18, 2019
4 Resources
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Publicly accessible
4 Resources
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Publicly accessible
Modeling Responses of Naturally Fractured Geothermal Reservoir to Low-Pressure Stimulation
Hydraulic shearing is an appealing reservoir stimulation strategy for Enhanced Geothermal Systems. It is believed that hydro-shearing is likely to simulate a fracture network that covers a relatively large volume of the reservoir whereas hydro-fracturing tends to create a small nu...
Fu, P. and Carrigan, C. Lawrence Livermore National Laboratory
Jan 01, 2012
2 Resources
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Publicly accessible
2 Resources
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Publicly accessible
Triggered MEQ Events on LBNL Permanent Seismic Array, Brady's EGS, March 2016
List of triggered events recorded on LBNL's permanent EGS seismic array at Brady's geothermal field. This submission also includes links to the NCEDC EGS Earthquake Catalog Search page and to the metadata for the seismic array installed at Brady's Geothermal Field.
Robertson, M. University of Wisconsin
Jun 01, 2016
3 Resources
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3 Resources
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Publicly accessible
Newberry EGS Seismic Velocity Model
We use ambient noise correlation (ANC) to create a detailed image of the subsurface seismic velocity at the Newberry EGS site down to 5 km. We collected continuous data for the 22 stations in the Newberry network, together with 12 additional stations from the nearby CC, UO and UW ...
Templeton, D. Lawrence Livermore National Laboratory
Oct 01, 2013
1 Resources
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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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3 Resources
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Fully Coupled Geomechanics and Discrete Flow Network Modeling of Hydraulic Fracturing for Geothermal Applications
The primary objective of our current research is to develop a computational test bed for evaluating borehole techniques to enhance fluid flow and heat transfer in enhanced geothermal systems (EGS). Simulating processes resulting in hydraulic fracturing and/or the remobilization of...
Fu, P. et al Lawrence Livermore National Laboratory
Jan 01, 2011
2 Resources
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2 Resources
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Utah FORGE: 2024 Discrete Fracture Network Model Data
The Utah FORGE 2024 Discrete Fracture Network (DFN) Model dataset provides a set of files representing discrete fracture network modeling for the FORGE site near Milford, Utah. The dataset includes four distinct DFN model file sets, each corresponding to different time frames and ...
Finnila, A. and Jones, C. Energy and Geoscience Institute at the University of Utah
Sep 08, 2024
5 Resources
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5 Resources
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Simulating Complex Fracture Systems in Geothermal Reservoirs Using an Explicitly Coupled Hydro-Geomechanical Model
Low permeability geothermal reservoirs can be stimulated by hydraulic fracturing to create Enhanced (or Engineered) Geothermal Systems (EGS) with higher permeability and improved heat transfer to increase heat production. In this paper, we document our effort to develop a numerica...
Carrigan, C. et al Lawrence Livermore National Laboratory
Jan 01, 2011
2 Resources
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2 Resources
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Utah FORGE: 2022 Seismic Workshop Report
Utah FORGE held a two-day seismic workshop on the University of Utah campus in Salt Lake City, Utah on September 26 and 27, 2022 to share what was learned from the seismic monitoring during the 2022 stimulation. This is a report documenting this workshop. The meeting was structure...
Pankow, K. University of Utah Seismograph Stations
Dec 19, 2022
1 Resources
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1 Resources
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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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4 Resources
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Utah FORGE: Microseismic Surface Network Catalogs for Wells 16A(78)-32 and 16B(78)-32 Stimulation 2022 and Circulation 2023
This dataset includes microseismic surface network catalogs for Utah FORGE. Data were recorded during the stimulation of well 16A(78)-32 in 2022 and the circulation tests between wells 16A(78)-32 and 16B(78)-32 in 2023. Near-surface seismic monitoring during circulation experimen...
Niemz, P. et al University of Utah Seismograph Stations
Feb 09, 2024
1 Resources
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1 Resources
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Utah FORGE: Evaluation of Potential Geochemical Responses to Injection in the FORGE Geothermal Reservoir
Plugging of fracture porosity from mineral precipitation due to injecting cold water into a a geothermal reservoir can impact the overall permeability of the fracture network in the reservoir. This can have serious ramifications on the efficiency of the geothermal resource. Geoche...
Patil, V. and Simmons, S. Energy and Geoscience Institute at the University of Utah
Apr 03, 2019
1 Resources
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1 Resources
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Improved Microseismicity Detection During Newberry EGS Stimulations
Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are oft...
Templeton, D. Lawrence Livermore National Laboratory
Oct 01, 2013
1 Resources
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1 Resources
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Utah FORGE 4-2492: Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery 2024 Annual Workshop Presentation
This is a presentation on the Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery Efficiency by The University of Texas at Austin, presented by Mukul M. Sharma. This video slide presentation discusses the following objectives: (1) to place fr...
Sharma, M. Energy and Geoscience Institute at the University of Utah
Sep 16, 2024
1 Resources
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1 Resources
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Improved Microseismicity Detection During Newberry EGS Stimulations
Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are oft...
Templeton, D. Lawrence Livermore National Laboratory
Nov 01, 2013
1 Resources
0 Stars
Publicly accessible
1 Resources
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Publicly accessible