Improved Genetic Algorithm for Injection Production Parameters Optimized Design of Steam Soak Well

Tian Jian Sun; Jun Feng Shi; Lei Xu

doi:10.4028/www.scientific.net/AMR.466-467.435

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 466-467Improved Genetic Algorithm for Injection...

Improved Genetic Algorithm for Injection Production Parameters Optimized Design of Steam Soak Well

Abstract:

He development effect of steam soak well is influenced by the combination of the following parameters: injection speed, dryness fraction of steam, cyclic steam injection volume, soaking time and bottom hole flowing pressure. Take the advantage of annealed genetic algorithm which characterize with the traits of fast search and globally optimization. Based on the mathematical model of the output of the steam soak well, and optimize injection production parameter of the steam soak well which is aimed at the cycle average daily profit maximum, and make the field application.

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Periodical:

Advanced Materials Research (Volumes 466-467)

Pages:

435-439

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.466-467.435

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Online since:

February 2012

Authors:

Tian Jian Sun, Jun Feng Shi, Lei Xu

Keywords:

Genetic Algorithm (GA), Injection Production Parameter, Optimized Design, Team Soak

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References

[1] Wang Zuwen, Wang Xinhai, Li Hong. Numerical Simulation on Steam Soak in Sensitivity Heavy Oil Reservoirs of Fault Block Z411[J], Li Hong. Journal of Daqing Petroleum Institute, 2005, 28（1）: 118~120.

Google Scholar

[2] Wang Xiaoping, Cao Liming. Genetic Algorithm: theory, principle and Software realization[M]. Xi'an, Xi'an jiaotong university press, 2002: 18~49.

Google Scholar

[3] Zhang Jiangshe. Overall annealing genetic algorithm and its convergence theory[J], China science (E), 1997, 27（2）: 154~164.

Google Scholar

[4] Xu Zongben. Genetic algorithm is premature convergence analysis of characteristics and prevention of the phenomenon[J], China science (E), 1996, 26（4）: 364~375.

Google Scholar

[5] Chen Yueming. Thermal recovery steam injection[M]. Beijing: University of Petroleum Press, 1996. 86~125.

Google Scholar

[6] Liu Wenzhang. Heavy oil steam injection thermal recovery engineer [M]. Beijing: University of Petroleum Press, 1997. 247~278.

Google Scholar