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Programs and Code for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
710.72 kB
Publicly accessible
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...
Authors
Moraga, J. Colorado School of Mines
geothermalenergycodershell scriptsgeothermal aimachine learningself organizing mapk-meanspythonaiartificial intelligencedeep learningexplorationgeothermal explorationremote sensingblindsite detectionlstland surface temperaturenumpyrastertensorflowk meananomaly detectionlandsat adr lstsbatchslurmshell

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Apr 04, 2022
1.04 GB
Publicly accessible
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...
Authors
Ahmmed, B. Stanford University
geothermalenergymachine learningartificial intelligenceaiexplorationmodelmodelingprocessed datatraining datatraining datasetremote sensinghidden geothermal resourcesresource detectiondiscoverydevelopmentresourceneural networkprediction

U.S. Geothermal Heat Pump Siting Regulation and Zoning Ordinances (2026)

Sep 21, 2026
95.6 MB
Curated
This is a collection of documented state and local ordinances governing geothermal heat pumps (GHPs), ground-source heat pumps, and related geothermal exchange wells and loop systems throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance...
Authors
Pinchuk, P. et al National Laboratory of the Rockies
geothermalheatpumpexchangegeo-exchangeheatingcoolingwellclosed loopopen loophorizontal loopvertical loopordinanceregulationsetbacknoisepermittingaillmcompassinfra-compassmachine readablegeothermal heat pumpghpartificial intelligenceheating and cooling

U.S. Geothermal Electricity Siting Regulation and Zoning Ordinances (2026)

Sep 21, 2026
38.41 MB
Curated
This is a collection of documented state and local ordinances governing utility-scale geothermal electricity projects throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, wh...
Authors
Pullutasig, B. et al National Laboratory of the Rockies
geothermalenergypowerutilitywellexplorationdrillingnoisesetbackspermitssitinglocalcitationsaillmcompassinfra-compassmachine readableartificial intelligencewell drillingpower plantspower production

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

Oct 01, 2021
5.68 MB
Publicly accessible
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...
Authors
Siler, D. et al United States Geological Survey
geothermalenergynmfkbrady hot springsmachine learningmlbhsnonnegative matrix factorization k-meanshydrothermalbradyk-meansclusteringnonnegative matrix factorizationmatrix factorizationgeothermalcloudsmarttensorsunsupervised3d well data3d geologic mapgeologic structurefaultsstressgeologycharacterizationgeologic modelproductioncode

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

Apr 15, 2022
113.79 MB
Publicly accessible
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...
Authors
Jin, W. et al Idaho National Laboratory
reservoir thermal energy storagestochastic simulationgeotesmachine learningmodelingtesht-rtescharacterizationnumerical modelstochastichydrogeologic formationsimulated datasimulation datahigh-temperaturethermal energy storageoptimizationartificial neural network regressionannneural networkoperation scenariosseasonal-cyclepareto frontsseasonal operationcontinuous operationfalconmoose