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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

OwnerNational Renewable Energy Laboratory (NREL) - view all

Update frequencyunknown

Last updatedabout 1 year ago

Format

Overview

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 Discovery, Exploration, and Development of Hidden Geothermal Resources.

AI artificial intelligence development discovery energy exploration geothermal hidden geothermal resources machine learning model modeling neural network processed data remote sensing resource resource detection training data training dataset

Additional Information

KeyValue

dcat_issued2022-04-04T06:00:00Z

dcat_modified2022-05-26T16:04:57Z

dcat_publisher_nameStanford University

guidhttps://data.openei.org/submissions/5710

ib1_trust_framework[]

language

Files

hdf5
AR Training Dataset 3D_diff.hdf5
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jl
GeoThermalCloud GitHub
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TXT
Parameters Documentation.txt
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