Production Optimization under Uncertainty - Applied to Petroleum Production

A key challenge in production optimization is handling of model uncertainty. Traditionally, production optimization is done in a deterministic setting, ignoring the uncertainty. In this work, we formulate the problem as a two-stage stochastic programming problem. The solution to the problem is a strategy for operating the wells, instead of a single setpoint obtained from the deterministic problem. This strategy is easy to follow for the operator. A synthetic case study shows how the proposed approach increases the expected oil production by 1.5 percent.