A Nonlinear Approach to Gas Lift Allocation Optimization With Operational Constraints Using Particle Swarm Optimization and a Penalty Function

摘要

Most gas lift well networks confront the limitations of both gas supply and compressor capacity. Thus, simultaneously allocating a number of the wells the optimum of the gas injection rate and the gas injection depth to reach the maximum oil production, in addition to satisfying the stated constraints, is the most important effort for the design process. This novel approach is a modification of the conventional allocation optimization problem in which no constraint on the gas injection pressure at the surface was considered. In this work, a model using a particle swarm optimization algorithm and penalty function method is presented to solve the new approach of the allocation optimization problem with high speed and desirable accuracy. Then the model is tested on a group of wells.