Numerical simulation and optimization of steam-assisted gravity drainage with temperature,rate, and well distance control using an efficient hybrid optimization technique

Steam-assisted gravity drainage (SAGD) is a thermal enhanced oil recovery technique through drilling of two horizontal wells. Effects of steam injection temperature, well rates, and their distance on oil recovery were analyzed and optimized. Steam temperature and well distances remarkably affect SAGD performance. Four metaheuristic algorithms (particle swarm optimization (PSO), imperialist competitive algorithm, cultural algorithm, and Bees algorithm) and pattern search optimization algorithm (PSA) are used for optimization. PSO performs better than other metaheuristics and PSA is the fastest one, while it is probable to be trapped in local optimums. Hybrid PSO-PS is proposed that starts with PSO and proceeds with PSA, and tested in an SAGD project and showed excellence over other techniques.