Well placement optimization using direct mapping of productivity potential and threshold value of productivity potential management strategy

ABSTRACT Well placement optimization is usually complex, nonlinear and multimodal in oil field development. Well placement is usually optimized by coupling reservoir numerical simulator with population-based algorithms. This method is computationally expensive, as they require many fitness function calls during the optimization process which limits its optimization efficiency. In this work, the direct mapping of productivity potential (DMPP) technique is applied for well placement optimization problems. Threshold value of productivity potential (TVPP) coupled with particle swarm optimization (PSO) is first proposed as a screening process to reduce the number of objective function evaluation based on DMPP. PUNQ-S3 model is applied to analyze the adaptability of DMPP and feasibility of TVPP for well placement optimization. Results demonstrate TVPP management strategy can significantly reduce the optimization time (OT) and keep the optimization effect at the same time. Taken it total, the proposed management strategy is simple but very efficient.