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Distributed Acoustic Sensing (DAS) for Periodic Hydraulic Tests: Laboratory Data
These data were collected in the laboratory located at California State University Long Beach. They consist of DAS data collected from a fiber optic cable placed in a tank of water, subjected to oscillating head. These tests are described in the article linked below.
Coleman, T. California State University
Feb 27, 2015
5 Resources
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5 Resources
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Open Water Rate Specification
This repository documents the Open Water Rate Specification (OWRS), a machine-readable format for specifying and sharing water rate information. OWRS is designed for analysts, economists, and software developers interested in analyzing water rates. OWRS attempts to fully encode a ...
Staff, C. National Renewable Energy Laboratory
Feb 29, 2016
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In curation
5 Resources
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In curation
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
2 Resources
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2 Resources
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Utah FORGE: Phase 3 InSAR Study Results
Ground movement is evaluated through analysis of Interferometric Synthetic Aperture Radar (InSAR) interferograms. Results indicate there has been no detectable ground movement at millimeter scale. The zipped file in this submission contains a report, maps, and results from the InS...
Feigl, K. and Batzli, S. Department of Geoscience University of Wisconsin-Madison
Sep 24, 2020
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Water chemistry data and calculations for Fracture Sustainability Tests
Measured cation, anion, and silica are presented as well as calculations evaluating mass balance performed for 4 fracture sustainability tests under EGS conditions: Stripa granite, Metamudstone, Rhyolitic Ashflow Tuff, and Silicified Rhyolitic Tuff. Calculations of charge balance ...
Kneafsey, T. et al Lawrence Berkeley National Laboratory
Sep 30, 2020
2 Resources
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2 Resources
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Utah FORGE: Phase 3 Microgravity Data
A 4D microgravity survey began in early 2019 in order to benchmark surface and subsurface elevations prior to Phase 3 drilling and stimulation campaigns. Microgravity stations are collocated with GPS deformation benchmarks and use the same location survey data. Surveys are underta...
Hardwick, C. Utah Geological Survey
Oct 07, 2020
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Purdue University: Results of B-Value Tests for Rock Saturation
This dataset includes an Excel file with the results of B-value tests to determine the magnitude of the back pressure required for full saturation of Sierra White granite samples. Test were conducted on cylindrical rock specimens of Sierra White granite in a custom water pressuriz...
Han, K. et al Purdue University
Jun 20, 2022
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2 Resources
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Utah FORGE Phase 3 Native State Model: 2022 Update
This is the Phase 3 native state model update. The Phase 3 numerical model represents a significant subsurface volume below the FORGE site footprint. The model domain of 4.0 km x 4.0 km x 4.2 km is located approximately between depths of 4000 to 4200 meters below land surface. Thi...
Podgorney, R. and Liu, R. Idaho National Laboratory
Jul 29, 2022
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Chemistry of the thermal water samples of the Camas Prairie area in Idaho, USA
This dataset includes chemistry of geothermal water samples of the Camas Prairie area in Idaho. The samples included in this dataset were collected over the period of 2016-2019. Collection/analysis of new water samples and compilation of existing water chemistry database were cond...
Neupane, G. et al Idaho National Laboratory
Sep 30, 2020
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Machine Learning Model Geotiffs Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains geotiffs, supporting shapefiles and readmes for the inputs and output models of algorithms explored in the Nevada Geothermal Machine Learning project, meant to accompany the final report. Layers include: Artificial Neural Network (ANN), Extreme Learning Ma...
Faulds, J. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
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EGS Collab Experiment 2: Wireline Geophysical Well Logs
This is the full wireline geophysical datasets for characterization of the EGS Collab Experiment #2 testbed. A metadata fill is included within the dataset explaining the logs, fracture picks, etc. Eleven boreholes were drilled for this testbed and each one was logged with north s...
Ulrich, C. and Schwering, P. Lawrence Berkeley National Laboratory
Jul 09, 2019
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Utah FORGE 2-2404: Determination of Reservoir-Scale Stress State Presentation Slides
This PowerPoint summarizes the integration of multiple approaches and data to constrain wellbore stress models at Utah FORGE. This stress determination used faulting theory, breakouts, and drilling-induced cracks detected in image logs. Wellbore stress profiles were established f...
Ghassemi, A. et al The University of Oklahoma
Jul 31, 2022
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UAE6 Wind Tunnel Tests Data UAE6 Sequence 4 Raw Data
**Overview**
Sequence 4: Static Pressure Calibration (P)
This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed
ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 30° were achieved. The blade tip pitch was 3°.
The rotor rotated at 72 RPM. B...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 28, 2018
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UAE6 Wind Tunnel Tests Data UAE6 Sequence 6 Raw Data
**Overview**
Sequence 6: Shroud Wake Measure (P)
This test sequence used a downwind, rigid turbine with a 3.4° cone angle. The wind speeds for
this sequence corresponded to subcritical [7 m/s], transitional [15 m/s], and supercritical [20 m/s]
Reynolds number regimes for the ci...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 28, 2018
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UAE6 Wind Tunnel Tests Data UAE6 Sequence F Raw Data
**Overview**
Sequence F: Downwind High Cone (F)
This test sequence used a downwind, rigid turbine with an 18° cone angle. The wind speed
ranged from 10 m/s to 20 m/s. Excessive inertial loading due to the high cone angle prevented
operation at lower wind speeds. Yaw angles of Â...
Fingersh, L. Wind Energy Technologies Office (WETO)
Nov 27, 2018
1 Resources
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Sodar Cleburne, TX Processed Data
**Overview**
This dataset was produced from the raw sodar .dat files from the Cleburne, TX site during the WFIP1 campaign. Quality control and formatting have been applied to transform the numerous raw files into a single file to provide user friendliness and improved wind resour...
Sheridan, L. Wind Energy Technologies Office (WETO)
Jul 17, 2011
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Sodar Ozona, TX Processed Data
**Overview**
This dataset was produced from the raw sodar .dat files from the Ozona, TX site during the WFIP1 campaign. Quality control and formatting have been applied to transform the numerous raw files into a single file to provide user friendliness and improved wind resource ...
Sheridan, L. Wind Energy Technologies Office (WETO)
Jul 17, 2011
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Sodar Reagan, TX Processed Data
**Overview**
This dataset was produced from the raw sodar .dat files from the Reagan, TX site during the WFIP1 campaign. Quality control and formatting have been applied to transform the numerous raw files into a single file to provide user friendliness and improved wind resource...
Sheridan, L. Wind Energy Technologies Office (WETO)
Aug 03, 2011
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Lidar HilFlowS LLNL ZephIR300 MOP Processed Data
**Overview**
The ZephIR300 is a continuous wave LIDAR with a range of 10 m to 300 m. During HilFlowS the ZephIR300 was programmed to measure from 10 m to 150 m. In addition, the ZephIR300 provided a measurement at 1 m height using an onboard meteorological sensor. The ZephIR300 ...
Wharton, S. and , . Wind Energy Technologies Office (WETO)
Jul 07, 2019
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Lidar HilFlowS LLNL ZephIR300 WOP Processed Data
**Overview**
The ZephIR300 is a continuous wave LIDAR with a range of 10 m to 300 m. During HilFlowS the ZephIR300 was programmed to measure from 10 m to 150 m. In addition, the ZephIR300 provided a measurement at 1 m height using an onboard meteorological sensor. The ZephIR300 ...
Wharton, S. and , . Wind Energy Technologies Office (WETO)
Jul 07, 2019
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Lidar ND Halo Scanning Doppler, Boardman Reviewed Data
**Overview**
The University of Notre Dame (ND) scanning LiDAR dataset used for the WFIP2 Campaign is provided. The LiDAR is a Halo Photonics Stream Line Scanning Doppler LiDAR.
**It is highly recommended to discuss any planned use of these data with University of Notre Dame scie...
Fernando, J. et al Wind Energy Technologies Office (WETO)
Dec 12, 2015
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wfip2.model/retro.hrrr.01.fcst.01
**Overview**
The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
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wfip2.model/retro.hrrr.01.fcst.02
**Overview**
The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
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wfip2.model/retro.hrrr.02.fcst.01
**Overview**
The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
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wfip2.model/retro.hrrr.02.fcst.02
**Overview**
The primary purpose of WFIP2 Model Development Team is to improve existing numerical weather prediction models in a manner that leads to improved wind forecasts in regions of complex terrain. Improvements in the models will come through better understanding of the ph...
Macduff, M. Wind Energy Technologies Office (WETO)
Feb 09, 2016
1 Resources
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1 Resources
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