CX-101531: Geothermal Operational Optimization with Machine Learning (GOOML)

Award Number: DE-EE0008766
CX(s) Applied: A9
Geothermal Technologies Office
Location(s): Mult
Office(s): Golden Field Office

The U.S. Department of Energy (DOE) is proposing to provide funding to Upflow Ltd. to develop machine learning algorithms to increase geothermal operational efficiency. Field production data would be sourced from existing geothermal fields in New Zealand, California, and Nevada. This data would then be used to develop algorithms which could identify opportunities for increased geothermal efficiency, detect hazards/risks, and enable predictive scenario modeling. Data gathering would be limited to steam field operations (e.g. well flows, separation pressures and mass flow), and would not include drilling operations or exploration activities. The project would be completed over two Budget Periods (BPs), with a Go/No-Go Decision Point in between each BP.