GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework and fictional input data, and a genetic optimization is included which determines optimal flash plant parameters. The inputs and outputs associated with the forecast and genetic optimization are included. The input and output files consist of data, configuration files, and plots.

A link to the Physics-Guided Neural Networks (phygnn) GitHub repository is also included, which augments a traditional neural network loss function with a generic loss term that can be used to guide the neural network to learn physical or theoretical constraints. phygnn is used by the GOOML framework to help integrate its machine learning models into the relevant physics and engineering applications.

Note that the data included in this submission are intended to provide a demonstration of GOOML's capabilities. Additional files that have not been released to the public are needed for users to run these models and reproduce these results.

Units can be found in the readme data resource.

Data e Risorse

Campo Valore
DOI 10.15121/1812319
accessLevel public
bureauCode {019:20}
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dataQuality true
identifier https://data.openei.org/submissions/4472
issued 2021-06-30T06:00:00Z
landingPage https://gdr.openei.org/submissions/1314
license https://creativecommons.org/licenses/by/4.0/
modified 2021-11-24T22:37:44Z
old-spatial {"type":"Polygon","coordinates":[[[-180,-83],[180,-83],[180,83],[-180,83],[-180,-83]]]}
programCode {019:006}
projectLead Angel Nieto
projectNumber EE0008766
projectTitle Geothermal Operational Optimization with Machine Learning (GOOML)
publisher Upflow
resource-type Dataset
source_datajson_identifier true
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Gruppi
  • AmeriGEOSS
  • National Provider
  • North America
Tag
  • amerigeo
  • amerigeoss
  • big-kahuna
  • ckan
  • code
  • configuration
  • data
  • energy
  • example
  • flash-plants
  • forecast
  • genetic-optimization
  • geo
  • geoss
  • geothermal
  • gooml
  • inputs
  • machine-learning
  • model
  • national
  • neural-network
  • north-america
  • operations
  • optimization
  • outputs
  • phygnn
  • physics-guided-neural-networks
  • power-plant
  • processed-data
  • python
  • simulation
  • steam-field
  • steamfield
  • synthetic-data
  • united-states
  • wells
isopen True
license_id cc-by
license_title Creative Commons Attribution
license_url http://www.opendefinition.org/licenses/cc-by
maintainer Paul Siratovich
maintainer_email paul.siratovich@upflow.nz
metadata_created 2025-11-20T15:47:07.184936
metadata_modified 2025-11-20T15:47:07.184940
notes This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework and fictional input data, and a genetic optimization is included which determines optimal flash plant parameters. The inputs and outputs associated with the forecast and genetic optimization are included. The input and output files consist of data, configuration files, and plots. A link to the Physics-Guided Neural Networks (phygnn) GitHub repository is also included, which augments a traditional neural network loss function with a generic loss term that can be used to guide the neural network to learn physical or theoretical constraints. phygnn is used by the GOOML framework to help integrate its machine learning models into the relevant physics and engineering applications. Note that the data included in this submission are intended to provide a demonstration of GOOML's capabilities. Additional files that have not been released to the public are needed for users to run these models and reproduce these results. Units can be found in the readme data resource.
num_resources 11
num_tags 36
title GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files