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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
Publicly accessible
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
Publicly accessible
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
Publicly accessible
Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
Williams, J. et al Global Technology Connection, Inc.
Jan 21, 2025
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
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
Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation 2024 Annual Workshop Presentation
This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, disc...
Dvory, N. Energy and Geoscience Institute at the University of Utah
Sep 15, 2024
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments
Active source ultrasonic data from lab experiments p5270 and p5271 including raw waveforms (WF) and mechanical data (mat). From the PSU team working on the "Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties" project. The fric...
Marone, C. Pennsylvania State University
May 05, 2021
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
Publicly accessible
6 Resources
0 Stars
Publicly accessible
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
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
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
Publicly accessible
Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
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
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Land of Opportunity: Geothermal, Land-based Wind, and Solar PV Potential on Federal Lands
This data packet contains supply curves and a composite siting exclusion TIFF for geothermal, land-based wind, and solar PV across the contiguous United States with specific consideration on federal lands. The supply curves offer comprehensive metrics such as capacity (MW) for eac...
Geospatial, N. National Renewable Energy Laboratory
Jan 01, 2025
28 Resources
0 Stars
Publicly accessible
28 Resources
0 Stars
Publicly accessible
Environmental Protection Agency (EPA) Renewable Energy Cost Database
The database is a compilation of existing cost data for wind, solar photovoltaic (solar PV), solar thermal (CSP), and geothermal energy technologies, including historical costs and projected costs for each. The data sources and references used to compile this information are inclu...
Hill, G. and Agency, E. National Renewable Energy Laboratory
Dec 31, 2009
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
University of Illinois Campus Deep Direct-Use Feasibility Study Long-Term Meteorological Data
This submission includes meteorological data recorded by National Weather Service at University of Illinois Willard Airport, Savoy IL for period 1972 to 2018. This data is for use in parameterizing the demand and life-cycle assessments associated with the project, and provides inf...
Lin, Y. University of Illinois
Mar 30, 2018
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Washington Play Fairway Analysis Poly 3D Matlab Fault Modeling Scripts with Input Data to Create Permeability Potential Models
Matlab scripts and functions and data used to build Poly3D models and create permeability potential layers for 1) St. Helens Shear Zone, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.
Swyer, M. et al AltaRock Energy Inc
May 01, 2017
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
EU Energy Statistics 2010 (1990 2007)
[European Commission]: http://ec.europa.eu/about_en.htm
These two datasets include energy statistics for the European Union (EU). The statistics are available from the [European Commission][]. The data includes detailed information about: production, net imports, gross inland con...
Hallett, K. and Commission, E. National Renewable Energy Laboratory
Jul 29, 2014
3 Resources
0 Stars
In curation
3 Resources
0 Stars
In curation
Washington Play Fairway Analysis Poly 3D Matlab Fault Modeling Scripts with Input Data to Create Permeability Potential Models
Matlab scripts and functions and data used to build Poly3D models and create permeability potential GIS layers for 1) Mount St. Helens seismic zone, 2) Wind River Valley, and 3) Mount Baker geothermal prospect areas located in Washington state.
Swyer, M. AltaRock Energy Inc
Feb 05, 2015
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
2020 Annual Technology Baseline (ATB) Cost and Performance Data for Electricity Generation Technologies
Starting in 2015 NREL has presented the Annual Technology Baseline (ATB) in an Excel workbook that contains detailed cost and performance data, both current and projected, for renewable and conventional technologies. The workbook includes a spreadsheet for each technology. This up...
Akar. . et al National Renewable Energy Laboratory
Jul 28, 2020
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
South Park Mountain Data: South Park, Colorado
South Park, Colorado data including "Live" data and plots, updated every 2 hours.
Daily plots and raw data files, are available from March 28, 1997 to yesterday.
Solar Calendars, are available from March 1997 to the present month.
Wind roses (monthly, seasonal, & yearly) are av...
McKenna and AndreasNational Renewable Energy Laboratory
Dec 17, 2014
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
2017 Annual Technology Baseline (ATB): Cost and Performance Data for Electricity Generation Technologies
Each year since 2015, NREL has presented Annual Technology Baseline (ATB) in a spreadsheet that contains detailed cost and performance data (both current and projected) for renewable and conventional technologies. The spreadsheet includes a workbook for each technology. This sprea...
Hand. . et al National Renewable Energy Laboratory
Aug 21, 2017
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Life Cycle Emissions Factors for Electricity Generation Technologies
This dataset consists of a table containing the distribution of literature estimates of greenhouse gas emissions for the following electricity generation and storage technologies: biopower, coal, concentrating solar power, geothermal, hydrogen storage, hydropower, lithium-ion batt...
Nicholson and HeathNational Renewable Energy Laboratory
Aug 23, 2021
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Utah FORGE 3-2417: Meteorological Data During 2024 Stimulation
This preliminary data archive includes meteorological data recorded at the Utah FORGE facility over the period of time including the 16A/16B stimulation activities, largely March/April/May of 2024. This information may prove useful for understanding seismic and other instrumentati...
Ajo-Franklin, J. Rice University
May 09, 2024
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible