U.S. DOE announces $3.6m funding opportunity in Machine Learning for Geothermal Energy
The U.S. Department of Energy announced up to $3.6 million for 4-6 projects that will focus on early-stage R&D applications in machine learning to develop technology improvements in exploration and operational improvements for geothermal resources.
In a release last week, the U.S. Energy Department announced up to $3.6 million for 4-6 projects that will focus on early-stage R&D applications in machine learning to develop technology improvements in exploration and operational improvements for geothermal resources. The rapidly advancing field of machine learning offers substantial opportunities for technology advancement and cost reduction throughout the geothermal project lifecycle, from resource exploration to power plant operations.
Through this funding opportunity announcement (FOA), DOE’s Office of Energy Efficiency and Renewable Energy Geothermal Technologies Office (GTO) will fund projects to support new analytical tools for finding and developing geothermal resources, to establish the practice of machine learning in the geothermal industry, and maximize the value of the rich datasets utilized in the geosciences.
GTO will provide funding in two areas:
- Topic 1: Machine Learning for Geothermal Exploration – GTO seeks projects that advance geothermal exploration through the application of machine learning techniques to geological, geophysical, geochemical, borehole, and other relevant datasets. Of particular interest are projects that will identify drilling targets for future work.
- Topic 2: Advanced Analytics for Efficiency and Automation in Geothermal Operations – GTO seeks projects that apply advanced analytics to power plant and other operator datasets, with the goal of improving operations and resource management.
For consideration of full application, applicants must submit their concept paper by 5 p.m. ET on Aug. 23, 2018 to be eligible to submit a full application. View the FOA and submission instructions.
Source: U.S. DOE