The Factor of Safety-Constrained Model Predictive Controller Design for Closed-Loop Reservoir Management

A closed-loop optimal control strategy is extensively used in all engineering disciplines to achieve desired control while maximizing performance. Balancing the economics and safety in petroleum reservoirs calls for a closed-loop control scheme in its operation. With the objective of maximizing the oil production rate (OP) and tracking the factor of safety (FoS) within the safety limit, a stochastic optimization-based model predictive controller (MPC) formulation is proposed in this paper. In this work, we build a deterministic proxy model for the OP and polynomial chaos expansion (PCE)-based model for the FoS with the well bottom hole pressure (well BHP) as the inputs using the CMG-STARS and FLAC3D simulator data. These models are used to formulate the MPC to determine the optimal dynamic well bottom hole pressure (MOP). Results are compared with a fixed MOP and to a static measure directly based on the PCE model of the FoS.