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

Description

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.

Resources

Name Format Description Link
0 Dataset of type HDF5 for training NN (neural network). The Parameters Documentation resource in this submission outlines the input and output parameters of the dataset. https://gdr.openei.org/files/1377/AR_dataset_3D_diff.hdf5
0 Geothermal Cloud for Machine Learning. Includes the code used in the GeoThermalCloud Project. https://github.com/SmartTensors/GeoThermalCloud.jl
47 This documentation explains the organization of the AR Training Dataset for the GeoThermalCloud Neural Network. Parameters detailed include the input and output parameters. https://gdr.openei.org/files/1377/ParametersDocumentation.txt

Tags

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

Topics

Categories