Research on Dynamic Optimization Model of Gas Field Development Scheme Based on Intelligent Algorithm

Guofeng Liang

doi:10.54097/93q5wt92

Authors

Guofeng Liang

DOI:

https://doi.org/10.54097/93q5wt92

Keywords:

Intelligent Algorithm, Gas Field Development, Dynamic Optimization, Genetic Algorithm, Particle Swarm Optimization, Production Scheduling

Abstract

This paper proposes a dynamic optimization model of gas field development scheme based on intelligent algorithm, which adopts the combination of GA and PSO, aiming to optimize gas field resource allocation and improve production scheduling efficiency. First, by constructing a mathematical model in the gas field development process, various optimization objectives and constraints are clarified; then, combining the advantages of GA and PSO, a hybrid optimization strategy is proposed, which enables the model to automatically adjust decisions in a complex and dynamic gas field development environment to obtain the optimal resource scheduling scheme. In the experiment, by constructing a typical scenario of gas field development for simulation verification, the results show that the proposed intelligent optimization model has achieved significant results in improving resource utilization and shortening production cycle. Compared with traditional optimization methods, the optimization efficiency of the algorithm is improved by 15% to 20%. In addition, this paper also discusses the practical application potential of intelligent algorithms in gas field development, and provides new ideas and methods for resource scheduling problems in other related fields.

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