Multi-objective reservoir production optimization: Minimizing CO2 emissions and maximizing profitability
Dean S. Oliver, Patrick N. Raanes, A. Skorstad, Jon Sætrom
Abstract
Large amounts of energy are consumed and greenhouse gasses are emitted in the process of extracting oil and gas from offshore fields. We investigate methods for solving the multi-objective production optimization for minimizing the emissions of CO 2 while maximizing economic profitability. Two scalarization methods for solving the multi-objective optimization problem — the weighted-sum method and the ϵ -constraint method — are evaluated for computational efficiency and interpretability of solutions on a simplified model of a North Sea oil field. The ϵ -constraint approach provided an easily interpretable optimization problem with the ability to specify a target reduction in CO 2 emissions, but was relatively expensive to apply. The weighted-sum approach was easier to implement and the cost to obtain a solution was less than the cost for the ϵ -constraint approach by a factor of approximately three. For the injection rate controls in our example application, there were gaps in the Pareto optimal solutions obtained using the weighted sum approach when large weights were applied to the emissions reduction objective function. • Simplified reservoir/energy models were used to investigate CO2 emission reduction. • Large reductions in CO2 emissions are obtainable for small reductions in NPV. • Two approaches to multi-objective optimization were compared. • The ϵ -constraint method was able to provide the entire Pareto front. • Despite limitations, the weighted-sum approach appears to be the most practical.