A novel multi-objective estimation of distribution algorithm for solving gas lift allocation problem

Gas lifting is a common practice in the oil industry. Using an appropriate gas lift injection rate can ensure that the desired oil production rate would be achieved. In the case of an oil field, the problem of distributing a certain amount of the available gas among a number of wells is formally known as a gas lift allocation problem. In this paper, a multi-objective optimization algorithm, based on the Gaussian Bayesian Networks and the Gaussian kernels, is proposed in order to determine the best injection points, considering multiple objective functions. Firstly, the problem is solved in a similar approach to the previous literature with similar gas lift data and similar function approximation method, to compare the performance of the proposed algorithm with the older ones. Thereafter, an extended problem is discussed, with minimizing the water production as a new optimization criterion. The developed multi-objective scheme is capable of handling and optimizing a gas-lift problem with several constraints and conflicting objectives such as controlling the gas usage and increasing theoil production, whereas in the conventional single-objective optimizations, any alteration in theconstraints demands a new optimization process and often there is no place for considering anadditional objective in the gas-lift allocation problem. The results obtained by the proposed optimization algorithm significantly overcame those reported in the previous similar literature. For a single-objective fifty-six well problem, the results exhibited 16.24% improvement in the total oil production.