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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Error-Level-Controlled Synthetic Forecasts for Renewable Generation
Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the imp...
Zhang, X. et al National Renewable Energy Laboratory (NREL)
Jun 01, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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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
1 Resources
0 Stars
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1 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
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4 Resources
0 Stars
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Brady Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Geochemistry and paleo-geothermal features Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains the geochemistry dataset and paleo-geothermal features (sinter, travertine, tufa) (shapefiles and symbology) used in the Nevada Geothermal Machine Learning project.
A submission linking the full GitHub repository for our machine learning Jupyter Notebooks...
Faulds, J. and Ayling, B. Nevada Bureau of Mines and Geology
Nov 01, 2020
2 Resources
0 Stars
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2 Resources
0 Stars
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Potential structures Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid...
Faulds, J. and Coolbaugh, M. Nevada Bureau of Mines and Geology
Feb 20, 2021
3 Resources
0 Stars
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3 Resources
0 Stars
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Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
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BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset
The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...
Tripp, C. et al National Renewable Energy Laboratory
Dec 30, 2022
9 Resources
1 Stars
Curated
9 Resources
1 Stars
Curated
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
Publicly accessible
12 Resources
0 Stars
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National Forest System Lands in geothermal potential area
A GIS layer from the BLM nationwide PEIS of lands within the U.S. National Forest system that contain geothermal potential. The GIS layer contains .SBX, .XML, .SHX, .DBF (.XLS), .PRJ, .SBN, and .SHP data.
### License Info
Made open by BLM. http://www.doi.gov/privacy.cfm
Hill, G. and (BLM), U. National Renewable Energy Laboratory
Jul 29, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Python Codebase and Jupyter Notebooks Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, a...
Brown, S. and Smith, C. Nevada Bureau of Mines and Geology
Jun 30, 2022
4 Resources
0 Stars
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4 Resources
0 Stars
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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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Publicly accessible
11 Resources
0 Stars
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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
4 Resources
0 Stars
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4 Resources
0 Stars
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Gulf of Mexico Outer Continental Shelf Mapping Data
The US Department of Interior's (DOI) Bureau of Ocean Energy Management, Regulation and Enforcement (BOEMRE) published geographic data of offshore activities in the Gulf of Mexico Outer Continental Shelf (OCS) area. The data were built from the Technical Information Management Sys...
Hallett, K. and (BOEMRE), U. National Renewable Energy Laboratory
May 30, 2007
14 Resources
0 Stars
In curation
14 Resources
0 Stars
In curation
Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak
The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model:
brady_som_output.gri, brady_som_output.grd, brady_som_output.*
desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Moraga, J. et al Colorado School of Mines
Sep 01, 2020
16 Resources
0 Stars
Publicly accessible
16 Resources
0 Stars
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NAWI Seedling Project: Foundational Control Methods for Water Treatment Systems Online Actuator and Sensor Data
This repository contains online actuator and sensor data and associated meta-data collected during the NAWI-funded seedling project with title: Foundational Control Methods for Water Treatment Systems. For detailed information on each dataset, please check the README included there.
Villez, K. et al Oak Ridge National Laboratory
Jan 01, 2020
7 Resources
0 Stars
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7 Resources
0 Stars
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Programs and Code for Geothermal Exploration Artificial Intelligence
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Moraga, J. Colorado School of Mines
Apr 27, 2021
11 Resources
0 Stars
Publicly accessible
11 Resources
0 Stars
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Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations: Data used in Geosphere Journal Article
This data submission is for Phase 2 of Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations, which focuses on multi-fluid (CO2 and brine) geothermal energy production and diurnal bulk energy storage in geologic settings that are suitable for ...
A., T. Lawrence Livermore National Laboratory
Jun 01, 2015
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
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Sup3rWind Data (CONUS)
This data contains paired European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) and the Wind Integration National Dataset Toolkit (WTK) images for 2007 and 2010 over two regions in the US, with domain sizes ~800x800 (latitudes from 25.89 to 41.58, and long...
Sinha, S. et al National Renewable Energy Lab NREL
Jul 16, 2024
6 Resources
0 Stars
Curated
6 Resources
0 Stars
Curated
Bureau of Land Management (BLM) Public Lands in geothermal potential area
The dataset is a GIS layer displaying BLM public lands that lie within an area that has geothermal potential. The GIS layer contains .SBX, .XML, .SHX, .DBF (.XLS), .PRJ, .SBN, and .SHP data.
### License Info
Open information http://www.doi.gov/privacy.cfm
Hill, G. and (BLM), U. National Renewable Energy Laboratory
Jul 29, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Net Shape Fabricated Low Cost MHK Pass-Through the Hub Turbine Blades with Integrated Health Management Technology
The primary objective of this project is to develop a three-blade MHK rotor with low manufacturing and maintenance costs. The proposed program will design, fabricate and test a novel half-scale low cost, net shape fabricated single piece three-blade MHK rotor with integrated healt...
Wess, D. ARL Penn State
Feb 09, 2016
24 Resources
0 Stars
Publicly accessible
24 Resources
0 Stars
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Closed BLM public lands: Areas of Critical Environmental Concern (ACEC)
A GIS layer of Areas of Critical Environmental Concern (ACEC) that are within public lands managed by the U.S. Bureau of Land Management (BLM). The GIS layers were used by BLM in the nationwide Geothermal Resources Leasing Programmatic Environmental Impact Statement (PEIS). Some o...
Hill, G. and (BLM), U. National Renewable Energy Laboratory
Jul 29, 2014
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
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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