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 Discovery, Exploration, and Development of Hidden Geothermal Resources.

Data and Resources

AR Training Dataset 3D_diff.hdf5hdf5
Dataset of type HDF5 for training NN (neural network). The Parameters...
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GeoThermalCloud GitHubjl
Geothermal Cloud for Machine Learning. Includes the code used in the...
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Parameters Documentation.txtTXT
This documentation explains the organization of the AR Training Dataset for...
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Additional Info

Field	Value
Source	https://gdr.openei.org/submissions/1377
Version
Author
Author Email
Maintainer
Maintainer Email
Shared (this field will be removed in the future)	Open
IB1 Sensitivity Class
IB1 Trust Framework
IB1 Dataset Assurance
IB1 Trust Framework
GUID	https://data.openei.org/submissions/5710
Language
dcat_issued	2022-04-04T06:00:00Z
dcat_modified	2022-05-26T16:04:57Z
dcat_publisher_name	Stanford University
ib1_trust_framework	[]