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Utah FORGE LBNL 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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Active Source 3D Seismic Tomography of Brady Hot Springs Geothermal Field, Nevada
We deployed a dense seismic array to image the shallow structure in the injection area of the Brady Hot Springs geothermal site in Nevada. The array was composed of 238 5 Hz, three-component nodal instruments and 8,700 m of distributed acoustic sensing (DAS) fiber-optic cable inst...
Parker, L. University of Wisconsin
Aug 09, 2017
1 Resources
0 Stars
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1 Resources
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Utah FORGE Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study
This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model was developed using RMS velocities of the seismic reflection su...
Vasco, D. and Chan, C. Array Information Technology
Apr 30, 2022
2 Resources
0 Stars
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2 Resources
0 Stars
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Sentinel-1 Input Data for PSInSAR Analysis
Files used to perform the Persistent Scatterer InSAR analysis with SARPROZ. The data is sourced from ESAs Sentinel-1 project and covers Brady Hot Springs and Desert Peak geothermal areas. The original titles are included for the Sentinel-1 data. The naming guide is included as a l...
Moraga, J. Colorado School of Mines
Apr 29, 2021
73 Resources
0 Stars
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73 Resources
0 Stars
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Brady's Geothermal Field Nodal Seismometer Active Source Data Sample
This data is in sac format and includes recordings of two active source events from 238 three-component nodal seismometers deployed at Bradys Hot Springs geothermal field as part of the PoroTomo project. The source was a viberoseis truck operating in P-wave vibrational mode and ge...
Feigl, K. University of Wisconsin
Mar 25, 2016
2 Resources
0 Stars
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2 Resources
0 Stars
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Generalized Displacement Correlation Method for Estimating Stress Intensity Factors
This paper presents a generalized form of the displacement correlation method (the GDC method), which can use any linear or quadratic finite element type with homogeneous meshing without local refinement. These two features are critical for modeling dynamic fracture propagation pr...
Fu, P. et al Lawrence Livermore National Laboratory
Jan 01, 2012
1 Resources
0 Stars
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1 Resources
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EGS Collab Experiment 2: Distributed Fiber Optic Temperature Data (DTS)
Distributed fiber optic sensing was an important part of the monitoring system for EGS Collab Experiment #2. A single loop of custom fiber package was grouted into the four monitoring boreholes that bracketed the experiment volume. This fiber package contained two multi-mode fiber...
Rodriguez Tribaldos, V. et al Lawrence Berkeley National Laboratory
Nov 08, 2022
10 Resources
0 Stars
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10 Resources
0 Stars
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PoroTomo: Horizontal Distributed Acoustic Sensing (DAS) Measurements During an M 2.3 Explosion
Included here are Distributed Acoustic Sensing (DAS) data collected by the horizontal DAS array at Brady's Hot Springs Geothermal Field. The system recorded this data during an M 2.3 explosion at the Nevada Test Site (NTS), which is located approximately 400km southeast of the fie...
Kratt, C. et al Center for Transformative Environmental Monitoring Programs (CTEMPs)
Dec 18, 2018
4 Resources
0 Stars
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4 Resources
0 Stars
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Brady's Geothermal Field Nodal Seismometer Data
This submission includes links to raw data, field notes, metadata, and p-wave arrival auto-picks from processed data (not provided) from the nodal seismometer array deployed at the PoroTomo Natural Laboratory in Brady's Hot Springs, Nevada during the March 2016 testing. The data i...
Parker, L. University of Wisconsin
Mar 30, 2016
7 Resources
0 Stars
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7 Resources
0 Stars
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EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper
Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5...
Guglielmi, Y. Lawrence Berkeley National Laboratory
Sep 24, 2020
9 Resources
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9 Resources
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Rare Earth Adsorption and Desorption with PEGDA Beads
We synthesized PEGDA polymer hydrogel beads for cell embedding and compared REE biosorption with these beads via a gravity-driven flow through setup. One way to set up a flow through system is by cell encapsulation into polymer beads with a column setup similar to that used in th...
Jiao, Y. et al Lawrence Livermore National Laboratory
Mar 01, 2017
1 Resources
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1 Resources
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EGS Collab Experiment 1: In-situ observation of pre-, co and post-seismic shear slip preceding hydraulic fracturing
Understanding the initiation and arrest of earthquakes is one of the long-standing challenges of seismology. Here we report on direct observations of borehole displacement by a meter-sized shear rupture induced by pressurization of metamorphic rock at 1.5 km depth. We observed the...
Guglielmi, Y. et al Lawrence Berkeley National Laboratory
May 22, 2018
2 Resources
0 Stars
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2 Resources
0 Stars
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Brady's Geothermal Field Nodal Seismometers Metadata
Metadata for the nodal seismometer array deployed at the POROTOMO's Natural Laboratory in Brady Hot Spring, Nevada during the March 2016 testing.
Metadata includes location and timing for each instrument as well as file lists of data to be uploaded in a separate submission.
Parker, L. University of Wisconsin
Mar 28, 2016
12 Resources
0 Stars
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12 Resources
0 Stars
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Brady's Geothermal Field DAS Vibroseis Data
The submitted data correspond to the monitored vibrations caused by a vibroseis seismically exciting the ground in the vertical direction and captured by the DAS horizontal and vertical arrays during the PoroTomo Experiment. The data also include a file with the acceleration recor...
Feigl, K. University of Wisconsin
Mar 25, 2016
11 Resources
0 Stars
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11 Resources
0 Stars
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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
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12 Resources
0 Stars
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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
0 Stars
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