Wind-powered reservoir management with application to robust multi-objective optimization

Abstract This paper addresses the challenge of incorporating offshore wind power into reservoir management. Traditionally, oil and gas production is powered by gas turbines. While stable, gas turbines are a major source of CO2 emissions. In contrast, wind power produces power with minimal emissions. However, due to its high variability and uncertainty, including it in the optimization of operational strategies over extended periods can be challenging. In this paper, the optimization of production strategies over an ensemble of realistic wind power series is investigated. The ensemble is generated by a mathematical model consisting of an autoregressive model with a seasonal trend. The model is conditioned on relevant wind speed data from the North Sea with Bayesian inference. The wind speed data is selected from the open-access NORA10EI dataset. The methodology developed in this paper is applied to a multi-objective optimization problem, focusing on studying the tradeoff between profit and emissions. A benchmark test reservoir model and a detailed CO2 emissions calculator are employed. In this scenario, wind power is combined with traditional gas power, and all results are compared with a reference where only gas power is used. The experiment indicates that it is not possible to reduce emissions by 40% without the use of wind power.