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Utah FORGE: Seismic Risk Trafic Light System Version 2

The report outlines the updated Traffic Light System (TLS) for the Utah FORGE project, which aims to mitigate seismic risks associated with Enhanced Geothermal Systems (EGS) operations. It integrates lessons from past operations, including stimulation and circulation experiments a...

Pankow, K. et al University of Utah Seismograph Stations

Jan 24, 2025
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Fracture Sustainability Test, Pre and Post-Test Photomicrographs

The primary objective of this research is to understand how different rock types, mineral and fluid compositions, and fracture surface textures determine the longevity of fracture apertures, so that selection of reservoir rock can be economically optimized to reduce future refract...

Dobson, P. et al Lawrence Berkeley National Laboratory

Sep 26, 2016
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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
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Fallon FORGE: LiDAR Acquisition and Processing Report

The data is associated to the Fallon FORGE project and includes LiDAR from the Navy GPO. Also included are geologic maps from the USGS and Nevada Bureau of Mines and Geology for the Fallon, NV area.

Bucher, K. et al Sandia National Laboratories

May 23, 2016
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Maui LiDAR

Light Detection and Ranging (LiDAR) data for the Maui study area in South Maui, collected by Watershed Sciences, Inc. (WS) on October 29th, 2011 and from November 7th, 2011 to November 10th, 2011.

Akerley, J. Ormat Nevada Inc

Nov 10, 2011
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Remote Sensing and Geology of Glass Buttes, Oregon

This data set includes Light Detection and Ranging (LiDAR) data, a remote sensing processing report, and a geologic map of the Glass Buttes study area for ORMAT. The total area flown for the LiDAR remote sensing was 86,631 acres to fully encompass the area of interest (84,849 ac...

Akerley, J. et al Ormat Nevada Inc

Jun 21, 2010
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Utah FORGE: Well 78B-32 Core Sample Petrographic Analysis Data

This dataset contains an overview of the petrographic, X-ray Diffraction and scanning electron microscopy analyses of core samples from Utah FORGE Well 78B-32 and related data as described in the .zip folder's Description below.

Jones, C. Energy and Geoscience Institute at the University of Utah

Feb 21, 2023
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Utah FORGE: Well 16A(78)-32 Core Analysis Results

This dataset features petrographic, X-Ray Diffraction (XRD), and Scanning Electron Microscopy Analyses of core samples from well 16A(78)-32, which serves as the injection well for the Utah FORGE Enhanced Geothermal System (EGS) project. In addition to an overview of the analysis,...

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

Sep 22, 2023
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Acquisition and Processing of a Detailed Aeromagnetic Survey Glass Buttes, Oregon

Using an ultra-light aircraft, a high-resolution aeromagnetic survey was carried out over Ormat Nevada's Glass Buttes project area in Oregon. Survey operations were completed on May 25, 2010. Average terrain clearance was 223 meters from the sensor. A total of 1,352 line-miles o...

Akerley, J. Ormat Nevada Inc

May 27, 2010
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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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Dynamic Earth Energy Storage: Terawatt-year, Grid-scale Energy Storage Using Planet Earth as a Thermal Battery (GeoTES): Phase I Project Final Report

Final report for the DOE GTO funded research on geologic thermal energy storage (GeoTES), or commonly known as reservoir thermal energy storage (RTES). The results described in this report shed light on various aspects of RTES including project siting, operational performance, m...

Atkinson, T. et al Idaho National Laboratory

Sep 02, 2022
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Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...

Jin, W. et al Idaho National Laboratory

Apr 15, 2022
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