Oil field optimization under price uncertainty

This paper presents a mixed integer programming model for optical development of an oil field under uncertain future oil prices. Based on a two-dimensional reservoir description, the model suggests decisions concerning both design and operation, and the objective is to maximise the expected net present value of the oil field. A finite set of oil price scenarios with associated probabilities is given, and the scenario and policy aggregation technique developed by Rockafellar and Wets is used for solving the problem. This technique is developed for the case of continuous variables, and in this paper, we discuss different methods for adapting the scenario aggregation approach to the case of mixed integer problems. This is done by utilizing the interaction between the continuous (production) and integer (design) variables. We present numerical experiments and conclude that scenario aggregation may be a suitable technique also for mixed integer problems.