The project, “Data Science for the Energy Transition,” is being funded through a 3-year grant with the National Science Foundation (NSF) and will offer undergraduate and master’s students specialised training in statistical and machine learning techniques for subsurface Geo-data. Fugro’s role as an industry partner on the project is to provide UH with real-world Geo-data and guidance on their use for hands-on training opportunities.
Advances in Geo-data science are needed to keep pace with the global demands for renewable energy sources, including offshore wind. Requiring extensive Geo‑data coverage over vast lease areas, innovative computing techniques can help operators shorten the development schedule by making critical information available more quickly. As an example, Fugro has developed a machine learning solution for mapping boulder fields from seafloor data to uniquely identify and analyse thousands of boulders. Accelerating the site investigation phase through this kind of automation helps lower capital investment and the levelized cost of energy for offshore wind projects.
“We are pleased to partner with UH on this project and are committed to advancing Geo-data analytics and computing skills in the energy sector,” said Jason Smith, Fugro’s Global Director for Geo‑data Analysis and Geoconsulting. “Conventional and renewable energy development benefits from more automated application of Geo-data. As a UH alumnus, I am proud to be leading Fugro’s involvement on this project and look forward to the partnership’s contribution toward a safe and liveable world.”