Improved Genetic Algorithm for Gas Well Production Dynamic Optimization Model

Abstract:

In this paper, An improved genetic algorithm that Powell genetic annealing exact penalty function method was proposed to deal with the non-linear characteristics in gas well production dynamic optimization model. The direct method with Powell to unconstrained optimization problems as a parallel operator as selection, crossover and mutation operator, was embedded into the basic genetic algorithm. Powell operator was defined in genetic algorithm and using annealing exact penalty function control penalty term, so the hybrid genetic algorithm for the global optimal solution to unconstrained optimization problem was made. The method avoided the difficulties of solving the model gradient, and effectively overcome searching local optimal solution and not high success probability by artificially giving more initial point to calculate and seek the optimal solution with Powell method. And the method significantly improved the convergence probability of the global optimal solution in the genetic algorithm. The method was practical and effective by analysis of examples, and it can give suggestion for gas well reasonable production system.

• Periodical: Advanced Materials Research (Volumes 524-527)
• Pages: 1178-1184
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.524-527.1178
• Online since: May 2012
• Authors: Xian Feng Ding
• Keywords: Exact Penalty Function, Genetic Algorithm (GA), Model, POWELL, Production

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