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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
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GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...

Buster, G. et al Upflow

Jun 30, 2021
11 Resources
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Colorado Heat Flow Data from IHFC

This layer contains the heat flow sites and data of the State of Colorado compiled from the International Heat Flow Commission (IHFC) of the International Association of Seismology and Physics of the Earth's Interior (IASPEI) global heat flow database. The data include different i...

E., R. Flint Geothermal, LLC

Feb 01, 2012
1 Resources
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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
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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
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Passive Seismic Emission Tomography Results at San Emidio Nevada

The utility of passive seismic emission tomography for mapping geothermal permeability has been tested at San Emidio in Nevada. The San Emidio study area overlaps a geothermal field in production since 1987 and another resource to the south of the production field. Passive seismic...

Warren, I. et al Ormat Technologies, Inc.

Dec 01, 2016
2 Resources
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Simulation Tools for Modeling Thermal Spallation Drilling on Multiple Scales

Widespread adoption of geothermal energy will require access to deeply buried resources in granitic basement rocks at high temperatures and pressures. Exploiting these resources necessitates novel methods for drilling, stimulation, and maintenance, under operating conditions that ...

Walsh, S. et al Lawrence Livermore National Laboratory

Jan 01, 2012
1 Resources
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Magnetotelluric Data Collected in 2016 over the San Emidio Geothermal Field in Nevada

This data set includes the magnetotelluric (MT) data collected from October 21 to November 9, 2016 over the San Emidio geothermal field in Nevada by Quantec Geoscience USA Inc. on behalf of US Geothermal Inc. as part of a project entitled "A Novel Approach to Map Permeability Usi...

Folsom, M. et al Ormat Technologies, Inc.

Nov 09, 2016
11 Resources
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Development of a Downhole Tool Measuring Real-Time Concentration of Ionic Tracers and pH in Geothermal Reservoirs

For enhanced or Engineered Geothermal Systems (EGS) geothermal brine is pumped to the surface via the production wells, the heat extracted to turn a turbine to generate electricity, and the spent brine re-injected via injection wells back underground. If designed properly, the sub...

Hess, R. et al Sandia National Laboratories

Mar 31, 2014
1 Resources
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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021 Version 2.0

This submission includes an update to the WHOLESCALESamples2021January.xls file where the strikes and dips initially reported have been corrected to comply with the right hand rule. The updated excel file and a link to the original submission are included in this report. The ori...

Kleich, S. et al University of Wisconsin Madison

Jan 12, 2021
2 Resources
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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
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WHOLESCALE Catalog of Rock Samples at San Emidio Nevada collected in January 2021

This submission contains information on thirty-six rock samples collected from San Emidio, Nevada during January, 2021 for Subtask 2.3 of the WHOLESCALE project. The following resources include a .zip of rock sample photos taken in the field, a .zip of rock sample photos taken in ...

Kleich, S. et al University of Wisconsin Madison

Jan 12, 2021
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Seismic Survey 2016 Data at San Emidio Nevada

Included here are seismic data recorded at the San Emidio Geothermal field in Nevada. This passive seismic data were collected as part of the DOE-funded Subsurface Technology and Engineering R&D (SubTER) project to advance imaging and characterization of geothermal permeability. ...

Lord, N. et al University of Wisconsin-Madison

Jan 05, 2016
4 Resources
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Seismic Survey 2016 Metadata at San Emidio, Nevada

1301 Vertical Component seismic instruments were deployed at San Emidio Geothermal field in Nevada in December 2016. The first record starts at 2016-12-05T02:00:00.000000Z (UTC) and the last record ends at 2016-12-11T14:00:59.998000Z (UTC). Data are stored in individual files in o...

Lord, N. et al University of Wisconsin

Dec 05, 2016
10 Resources
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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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Hybrid machine learning model to predict 3D in-situ permeability evolution

Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...

Elsworth, D. and Marone, C. Pennsylvania State University

Nov 22, 2022
4 Resources
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WHOLESCALE: Seismic Survey Data from San Emidio Nevada 2021

This dataset includes raw and processed seismic data from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 N, 119.409019 W. The first...

Lord, N. et al University of Wisconsin-Madison

Apr 06, 2021
6 Resources
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Snake River Plain FORGE: Site Characterization Data

The site characterization data used to develop the conceptual geologic model for the Snake River Plain site in Idaho, as part of phase 1 of the Frontier Observatory for Research in Geothermal Energy (FORGE) initiative. This collection includes data on seismic events, groundwater,...

Moos, D. and Barton, C. Idaho National Laboratory

Apr 18, 2016
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WHOLESCALE: Seismic Survey Metadata from San Emidio Nevada 2021

This is a collection of metadata from the 2021 seismic survey at the San Emidio geothermal field in Nevada. In April and May 2021, 37 tri-axial short period seismographs were deployed in a 1.8km diameter cluster centered on 40.367278 deg N, 119.409019 deg W. The first data record...

Lord, N. et al Department of Geoscience University of Wisconsin-Madison

Apr 06, 2021
10 Resources
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