Optimization design of counter-type full-bore fracturing sliding-sleeve

被引：0

作者：

Zhao C. ^{[1
,2
]}

Wang S. ^{[1
,2
]}

Pei X. ^{[1
]}

Wu Z. ^{[1
]}

Nie Y. ^{[1
]}

Zhou H. ^{[1
]}

Sun H. ^{[1
]}

Jiang X. ^{[3
]}

机构：

[1] Drilling Technology Research Institute, Sinopec Shengli Petroleum Engineering Co., Ltd., Dongying, 257000, Shandong

[2] Key Laboratory of Unconventional Oil and Gas Drilling and Completion Technology, China Petroleum and Chemical Industry Federation, Dongying, 257000, Shandong

[3] Sinopec Research Institute of Safety Engineering, Qingdao, 266000, Shandong

来源：

Shiyou Xuebao/Acta Petrolei Sinica | 2018年 / 39卷 / 04期

关键词：

Fracturing sliding-sleeve; Full-bore; Optimization; Particle swarm optimization algorithm; Response surface;

D O I：

10.7623/syxb201804012

中图分类号：

学科分类号：

摘要：

To improve the stepping pressure and structural strength of inner sliding sleeve, an optimization method was proposed for counter-type full-bore fracturing sliding-sleeve in this study. The steepest ascent experiment was designed to determine the optimum response region. The response surface method was adopted to build the second-order response models between significant factors and stepping pressure as well as the maximum stress of inner sliding sleeve during the movement, respectively, so as to analyze the influence of each factor on the responses. The objective function was determined using the linear weighting method, and the particle swarm optimization (PSO)algorithm was employed to search and obtain the optimum structural parameters of inner sliding sleeve. Based on the explicit dynamic method, the process of the ball driving inner sliding sleeve was stimulated. The results show that after optimization, the maximum stress of inner sliding sleeve during the movement is improved by 9.2%, while its stepping pressure is increased by 40%. The laboratory experiments indicate that after the optimization, the stepping pressure of inner sliding sleeve is increased by 44%, similar to the numerical stimulation result. It can be summarized that the combination of particle swarm optimization algorithm, steepest ascent design and response surface method is an effective method for optimizing the structural parameters of inner sliding sleeve. © 2018, Editorial Office of ACTA PETROLEI SINICA. All right reserved.

引用

页码：482 / 490

页数：8

共 24 条

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