Dynamic Optimization of Waterflooding With Smart Wells Using Optimal Control Theory

Abstract

Summary We used optimal control theory as an optimization algorithm for the valve settings in smart wells. We focused on their use in injectors and producers for the waterflooding of heterogeneous reservoirs. As a followup to an earlier intuitive optimization approach, a systematic dynamic optimization approach based on optimal control theory was developed. The objective was to maximize recovery or net present value of the waterflooding process over a given time period. We investigated the scope for optimization under purely pressure- and purely rate-constrained operating conditions, and concluded that: (1) for wells operating on bottomhole-pressure constraints, the benefit of using smart wells is mainly reduced water production rather than increased oil production, and (2) for wells operating on rate constraints, there is generally a large scope for accelerating production and increasing recovery, in combination with a drastic reduction in water production.