Research on the Optimization of Operating Parameters of Steam Injection Pipe Network

Authors

  • Junfeng Liu

DOI:

https://doi.org/10.62051/ijepes.v3n1.06

Keywords:

Pipe Network Optimization, Genetic Algorithm, Written in MATLAB

Abstract

Scientifically optimizing the design of the steam injection pipe network is an important way to improve economic benefits, enhance oil production efficiency, and reduce energy consumption. In the study of the optimal layout of the steam injection pipe network, the operating parameters and operation schemes of the oilfield steam injection system were optimized, and a mathematical model of wet steam flow in dendritic pipelines was established. The genetic algorithm code was written in MATLAB for optimization, and the results were compared with the current steam network layout. The reliability has been proven and can be used as a reference for future pipe network layout studies. Taking the minimum energy consumption loss in the steam injection process as the objective function, an appropriate genetic optimization algorithm was selected to solve the mathematical model for three well parameters. Corresponding constraints and optimization principles were established with the main purpose of reducing energy consumption and improving efficiency. The relevant steam injection parameters were optimized and calculated, and the site of the steam injection station was determined.

References

[1] Huang Shanbo, Xu Minghai, Chen Zefang, et al. Optimal design of steam injection pipe-station system in heavy oil field [J]. Oil-Gas Field Surface Engineering, 2000 (05), 19(5).

[2] Cao Di, Ma Guoguang, Zuo Min. Overall layout optimization of gathering and transportation pipe network based on genetic algorithm [J]. Liaoning Chemical Industry, 2016(09), 45(9).

[3] Xue Jiaqing. Principles and methods of optimization [M]. Beijing Metallurgical Industry Press, 1983:2-60.

[4] Chen Guoliang. Genetic algorithms and their applications [M]. Beijing: People's Posts and Telecommunications Press, 1996:1-100.

[5] Cuneyt F. Baxlam acci. Minimum-weight spanning tree algorithms A survey and empirical study J. Computers & Operations Research, 2001(28).

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Published

31-10-2024

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Section

Articles