Advanced Offshore Hazard Forecasting to Enable Resilient Offshore Operations

Abstract

Paper prepared for the Offshore Technology Conference, 2024. Hazards in the offshore environment can imperil successful energy operations, whether those operations are conventional, renewable, or for decarbonization. The expanding accessibility of data science and the advanced applications of machine learning (ML) models creates an opportunity to assess potential hazards and the infrastructure they impact. We present a use case demonstrating the combined application of published ML tools to U.S. federal waters of the Gulf of Mexico, an actively explored region for offshore energy that is affected by variable metocean conditions and geologic processes contributing to potential hazards.