Integrated Optimization of Hybrid Steam-Solvent Injection in Post-CHOPS Reservoirs Under Uncertainty

Abstract

Abstract In this paper, an integrated algorithm is proposed to optimize the hybrid steam-solvent injection-production schemes for post-CHOPS reservoirs under uncertainty. First of all, the newly developed pressure-gradient-based (PGB) sand failure criterion is employed to generate dendritic (or fractal-like) and regional wormhole networks, based on which the net present value (NPV) is defined and used as the objective function. A hybrid optimization technique based on the genetic algorithm (GA) is then integrated with the orthogonal array (OA) and Tabu search to maximize the objective function by rationalizing the injection and production parameters and simultaneously retarding the displacement front to extend the reservoir life under uncertainty. In a given CHOPS well, not only can the proposed method be used to determine the overall morphology of the wormhole network, including intensity and coverage, but also design, evaluate, and optimize performance of any potential EOR processes in a post-CHOPS reservoir within a unified, efficient, and accurate framework.