Paper Title:
Structure Optimization of Slip by the Combination of Artificial Neural Network and Genetic Algorithm
  Abstract

The bridge plug is a staple tool used in downhole operation and the performance of the slips has a directly influence on the oil well productivity and production safety. We raised an optimize method based on BP network and genetic algorithm to make sure the slips satisfy the high temperature and high pressure demands. Establishing the slips system and making finite element analysis by ANSYS, abtaining sixteen group datas to constitute the BP network training samples, establishing the BP simulation model reflecting curvature radius of the slip fluke, dip angle of the fluke, angle of the fluke and distance between flukes using nonlinearity mapping ability of the neural network, applying optimize design for the simulation model using global optimization ability of the genetic algorithm and abtaining the optimum structure parameters of the slip. The optimized results indicate the whole performance of the slips system has increased notably.

  Info
Periodical
Advanced Materials Research (Volumes 199-200)
Edited by
Jianmin Zeng, Zhengyi Jiang, Taosen Li, Daoguo Yang and Yun-Hae Kim
Pages
1223-1229
DOI
10.4028/www.scientific.net/AMR.199-200.1223
Citation
D. X. Li, H. L. Zhao, S. M. Zhang, D. Geng, X. L. Liu, S. J. Zheng, "Structure Optimization of Slip by the Combination of Artificial Neural Network and Genetic Algorithm", Advanced Materials Research, Vols. 199-200, pp. 1223-1229, 2011
Online since
February 2011
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Price
$32.00
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