Multi-objective Optimization of Brugge Field for Short-Term and Long-Term Waterflood Management

This study focuses on investigating different multi-objective functions for the short-term and the long-term waterflood management applied in Brugge field benchmark model using NSGA-II algorithm. The short-term waterflood management is defined using four time-steps for two-year period with total of 120 decision variables. Three multi-objective function optimization cases are investigated for the short-term study [i.e., maximizing total oil production and minimizing total water production (Case-1), maximizing total oil production and minimizing total water cut (Case-2) and maximizing total oil production, maximizing net present value (NPV) and minimizing total water cut (Case-3)]. The results show that the highest oil production obtained from the Pareto front is in Case-1 with small difference compared to the other two Cases. The highest NPV is also achieved in Case-1 because of lower water production and lower water injection compared to Case-2 and Case-3. Long-term multi-objective optimization study (Case-4) is then run using NSGA-II algorithm for ten years with 640 decision variables considering well completions control in the producers and the injection rates control in injectors. The Pareto optimal solutions obtained by NSGA-II algorithm have shown higher NPV results with 30% improvement compared to previous work (Foroud et al. in J Petrol Sci Eng 167:131–151, 2018). The study has demonstrated the convergence into different Pareto optimal solutions obtained by applying NSGA-II algorithm coupled with the reservoir simulation model for the different optimization cases using Brugge field benchmark model. The results obtained deliver good range of optimum conditions from which any appropriate operating solution can be selected based on the requirements of the decision maker.