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Utah FORGE: Distributed Acoustic Sensing Data 2022

This is a link to the website where Distributed Acoustic Sensing (DAS) seismic data, collected from wells 78-32 and 78B-32 during the Utah FORGE 2022 stimulation, is available for download. The data can be accessed at "Well 16A78-32 2022 Stimulation Seismicity Data" link in the su...

Pankow, K. University of Utah Seismograph Stations

Apr 29, 2022
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Initial 3D Gravity Results at Newberry

Initial 3D gravity results from Zonge Int'l recorded for the 4D EGS Monitoring project at Newberry, during stimulation of Well 55-29 by AltaRock Energy

Rose, K. National Energy Technology Laboratory

Jul 31, 2015
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Harsh Environment Sensors for Geothermal Applications

Technical papers detailing the development of harsh environment sensors for geothermal applications. Principle Investigator is Prof. Albert P. Pisano (University of California, Berkeley). Submission includes a paper about geothermal environmental exposure testing on encapsulant a...

Senesky, D. et al Regents of the University University of California

Jan 01, 2012
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Utah FORGE: Telluric Monitoring Experiment Transfer Functions

The Utah Frontier Observatory for Research in Geothermal Energy (FORGE) attempted a stimulation at well 16A(78)-32 during April and May 2022. We recorded telluric and magnetotelluric (MT) data before, during, and after the well stimulation experiment using the FORGE Telluric Monit...

Mendoza, K. and Wannamaker, P. Energy and Geoscience Institute at the University of Utah

May 27, 2022
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Matlab Scripts and Sample Data Associated with Water Resources Research Article

Scripts and data acquired at the Mirror Lake Research Site, cited by the article submitted to Water Resources Research: Distributed Acoustic Sensing (DAS) as a Distributed Hydraulic Sensor in Fractured Bedrock M. W. Becker(1), T. I. Coleman(2), and C. C. Ciervo(1) 1 California St...

Becker, M. and Coleman, T. California State University

Jul 18, 2015
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Utah FORGE: Neubrex Hydraulic Fracturing DAS Based Fluid Injection Efficiency and Plug Analysis Report

Report reviews results acquired by Neubrex using Distributed Acoustic Sensing of the 16B(78)-32 Hydraulic Fracturing operations, Stages 1-4. The DAS data acquisition, processing and analysis focuses on acoustic noise signatures during each stage and analyzes the acoustic noise pr...

Jurick, D. et al Neubrex Energy Services (US), LLC

Apr 26, 2024
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Utah FORGE 4-2492: Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery Workshop Presentation

This is a presentation on the Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery Efficiency at the Utah FORGE Site project by The University of Texas at Austin, presented by Professor Mukul M. Sharma. The project's objectives were to place f...

Sharma, M. The University of Texas at Austin

Sep 08, 2023
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Utah FORGE: 2023 Phase 3B Year 1 Annual Report

This report discusses the objectives, goals, accomplishments and results of Phase 3B Year 1 of the Utah FORGE project. The report includes infrastructure, seismic monitoring, modelling, external R&D, communications and outreach, data produced, lessons learned, conclusions, and pla...

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

Aug 09, 2023
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Utah FORGE: InSAR Data

This is the InSAR dataset used in Utah FORGE Phase 2C to augment ground deformation monitoring. It is accompanied by a README.txt file which contains an explanation of the data in the .zip archive.

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

Jul 01, 2019
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Utah FORGE: Well 16A(78)-32 2022 Stimulation Microseismic Report

This is a Utah FORGE well 16A(78)-32 stimulation microseismic detection and event location report from Silixa LLC. The report covers the digital acoustic sensing (DAS) data acquisition and analysis used to study microseismic events during the April, 2022 stimulations at well 16A(7...

LLC, S. Energy and Geoscience Institute at the University of Utah

Sep 26, 2022
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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
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3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...

Siler, D. and Pepin, J. United States Geological Survey

Oct 01, 2021
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EGS Collab Experiment 2: Shear Stimulation ERT Monitoring Data

This repository contains the electrical resistivity tomography (ERT) monitoring data that was collected before, during, and after shear stimulation attempts were conducted at EGS Collab. These tests were carried out on the SURF 4100 level during Experiment 2 in March, 2022. Flow a...

Johnson, T. Pacific Northwest National Laboratory

Mar 06, 2023
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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
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Brady's Geothermal Field DASH Resampled in Time

This submission includes a link to the DASH (Horizontal distributed acoustic sensing) data files that were resampled in time to 100 samples per second from the original 1000 samples per second files. Data is in 30 second Matlab files organized into directories by day. The README_D...

Feigl, K. University of Wisconsin

Jul 07, 2017
3 Resources
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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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Utah FORGE: GPS Data Deformation Monitoring

This data bundle contains raw GPS data files and resulting data using Trimble Business Center and NOAA OPUS to process the GPS data in spreadsheets with station coordinates and elevations. A map of station locations is included along with the final processing report which includes...

Erickson, B. and McKean, A. Energy and Geoscience Institute at the University of Utah

Jun 24, 2019
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Utah FORGE: High-Resolution DAS Microseismic Data from Well 78-32

This regards a high-resolution DAS microseismic dataset produced by Silixa from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. It is a very large dataset and as such it is currently not directly available on GDR. However, it is availabl...

Martin, T. and Nash, G. Energy and Geoscience Institute at the University of Utah

Oct 20, 2019
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Utah FORGE: Earthquake Catalog

This is the set of earthquake catalogs developed for the Utah FORGE project covering December of 2016 through March of 2018. These are discussed in the "Utah FORGE Phase 2B Final Topical Report," which can be found on GDR under id: 1038 (See link 'Final Topical Report' in resource...

Pankow, K. Energy and Geoscience Institute at the University of Utah

Mar 21, 2018
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Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...

Siler, D. et al United States Geological Survey

Oct 01, 2021
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Newberry EGS Demonstration: Stimulating the Existing Fracture Network Report

The Newberry Volcano EGS Demonstration in central Oregon, a 3 year project started in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ...

Cladouhos, T. et al AltaRock Energy Inc

Mar 10, 2014
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Utah FORGE: Downhole Geophone Seismic Data (August 2022)

This is a link to downhole geophone data collected by Schlumberger. These data were collected in the Utah FORGE deep seismic monitoring wells 58-32 and 56-32. The format is a standard SEGY and the units are bits. To convert to acceleration (m/s2) multiply by 2.333 x 10-7. Use one ...

Pankow, K. and Schlumberger, S. University of Utah Seismograph Stations

Aug 25, 2022
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EGS Collab Experiment 2: Earth Model Datasets

The EGS Collab Project performed a series of tests to increase the understanding the response of crystalline rock mass to stimulations and fluid circulation to efficiently implement enhanced geothermal systems (EGS) technologies. The EGS Collab team created two underground testbed...

Neupane, G. et al Idaho National Laboratory

May 29, 2022
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EGS Collab Experiment 1: Core Logs

Core logs from the EGS Collab project Experiment 1 for the stimulation (Injection) well (E1-I), the Production well (E1-P), and monitoring wells (E1-OT, E1-OB, E1-PST, E1-PSB, E1-PDT, and E1-PDB) on the 4850 Level of SURF (the Sanford Underground Research Facility), single PDF fil...

Dobson, P. et al Lawrence Berkeley National Laboratory

Apr 02, 2019
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kISMET Final Report and Highlights

The files in this submission describes the results of a series of stress measurement and hydraulic fracturing experiments conducted at the Sanford Underground Research Facility (SURF) in Lead, SD. This report describes the accomplishments of the kISMET (permeability (k) and Induce...

Oldenburg, C. et al Lawrence Berkeley National Laboratory

Oct 31, 2016
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