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Raft River Geothermal Area Logical and Fact Data Models
This submission includes fact and logical data models for geothermal data concerning wells, fields, power plants and related analyses at Raft River, ID. The fact model is available in VizioModeler (native), html, UML, ORM-Specific, pdf, and as an XML Spy Project. An entity-relatio...
Cuyler, D. Sandia National Laboratories
Jul 19, 2012
7 Resources
0 Stars
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7 Resources
0 Stars
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Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2000
6 Resources
0 Stars
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6 Resources
0 Stars
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Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk : FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk : FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal energy production. Phase 1 includes reservoir analyses to determine injector/producer well schemes that balance the generation of economically useful flow rates at the ...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
9 Resources
0 Stars
Publicly accessible
9 Resources
0 Stars
Publicly accessible
EGS Collab: 3D Geophysical Model Around the Sanford Underground Research Facility
This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P and S-wave seismic speeds on a 3D grid. The file has six columns and provides latit...
Chai, C. et al Lawrence Berkeley National Laboratory
Feb 06, 2019
3 Resources
0 Stars
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3 Resources
0 Stars
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations
Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: An Approach to Improve Energy Recovery and Mitigate Risk: FY1 Final Report
The purpose of phase 1 is to determine the feasibility of integrating geologic CO2 storage (GCS) with geothermal ...
A., T. Lawrence Livermore National Laboratory
Jan 01, 2012
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog from Double-Difference Seismic Tomography
This package contains a 3D Seismic velocity model and an updated microseismic catalog obtained for a double-difference seismic tomography study.
The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-wave velocity (km/s), P-wave velocity quality indicator (1 for we...
Chai, C. et al Oak Ridge National Laboratory
Jun 01, 2020
8 Resources
0 Stars
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8 Resources
0 Stars
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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
6 Resources
0 Stars
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6 Resources
0 Stars
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GeoVision: Harnessing the Heat Beneath Our Feet Analysis Inputs and Results
This submission includes input and results data from analysis done as part of the Geothermal Technology Office's Geothermal Vision Study (GeoVision). The submission includes data for both analysis of the electricity sector and the heating and cooling sector. For the electricity se...
Geothermal Technologies Office, U. National Renewable Energy Laboratory
Sep 30, 2019
16 Resources
0 Stars
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16 Resources
0 Stars
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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Distributed Acoustic Sensing Experiment Data from Garner Valley, California
In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes all DAS data recorded during the experiment.
The sampling rate ...
Lancelle, C. University of Wisconsin
Sep 11, 2013
14 Resources
0 Stars
Publicly accessible
14 Resources
0 Stars
Publicly accessible
Sample Data from a Distributed Acoustic Sensing Experiment at Garner Valley, California
In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes one 45 kN shear shaker (called "large shaker" on the basemap) test ...
Lancelle, C. University of Wisconsin
Sep 10, 2013
10 Resources
0 Stars
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10 Resources
0 Stars
Publicly accessible
EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography
This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Chai, C. et al Oak Ridge National Laboratory
Apr 20, 2020
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Analysis of Existing Data from a Distributed Acoustic Sensing Experiment at Garner Valley, California
In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes noise cross-correlation functions (NCF) . Each file includes a NCF ...
Zeng, X. University of Wisconsin
Mar 26, 2015
37 Resources
0 Stars
Publicly accessible
37 Resources
0 Stars
Publicly accessible