Research on modeling and application of multi-objective evolutionary algorithm for optimal well network placement

This paper systematically proposes a modeling and solving framework based on multi-objective evolutionary algorithm for the complex multi-objective problem of well network optimization during oil and gas field development. A mathematical optimization model that takes into account the actual engineering constraints is constructed for the multi-objectives of production maximization, development cost minimization, and environmental impact minimization in the well network layout, which fully reflects the complex relationship between the well distribution and the production capacity, investment, and ecological environment. On this basis, an improved multi-objective evolutionary algorithm is designed, which adopts innovative coding scheme and adaptability evaluation method to effectively improve the global search capability and convergence speed of the algorithm, and ensure the diversity and balance of the optimization solutions. Through numerical simulation and comparative analysis of typical oilfield development cases, the superior performance of the proposed method in optimizing the well network layout scheme is verified, which significantly improves the resource allocation efficiency and economic benefits, and at the same time reduces the environmental risks. The research results not only provide a scientific and reasonable decision support tool for well network optimization in oil and gas fields, but also provide a theoretical reference and practical reference for the design of algorithms and engineering applications of related multi-objective optimization problems, which has important academic value and application prospects.