Closed-loop workflow for short-term optimization of wind-powered reservoir management

This paper presents a closed-loop workflow for short-term optimization of reservoir management powered by offshore wind energy. Motivated by the need to reduce CO 2 emissions in the Norwegian oil and gas sector, the workflow integrates wind power forecasts into optimization of daily well control while adhering to a long-term production strategy optimized for economic output. The workflow utilizes coarsened reservoir models calibrated through ensemble-based data assimilation to minimize computational costs. A realistic benchmark model, Drogon, is used to demonstrate the methodology. The workflow dynamically adjusts well rates to align power demand with wind availability, minimizing reliance on gas turbines and thereby reducing emissions. The numerical experiment demonstrates the potential of the workflow by significantly reducing short-term emissions without compromising the NPV. • We introduces a closed-loop workflow for wind-powered reservoir management. • Utilize coarsened reservoir models calibrated with data assimilation to reduce computational costs. • Dynamically adjust well rates to align the power demand to the available wind power. • Numerical experiments demonstrates the potential of the workflow by significantly reducing short-term emissions without compromising the NPV.