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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 7898647, 8 pages
https://doi.org/10.1155/2017/7898647
Research Article

A New Mathematical Method for Solving Cuttings Transport Problem of Horizontal Wells: Ant Colony Algorithm

1School of Petroleum Engineering, China University of Petroleum, Qingdao 266580, China
2College of Energy Engineering, Yulin University, Yulin 719000, China
3Drilling Technology Research Institute, Shengli Petroleum Engineering Corporation, Sinopec, Dongying 257000, China
4Laojunmiao Oil Production Plant, Yumen Oilfield, Jiuquan 735000, China

Correspondence should be addressed to Liu Yongwang; moc.361@3002gnawgnoyuil

Received 19 March 2017; Revised 1 July 2017; Accepted 16 July 2017; Published 29 August 2017

Academic Editor: Jian G. Zhou

Copyright © 2017 Liu Yongwang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Z.-M. Wang and Z. Zhang, “Model for two-layer cutting transport in horizontal wells,” Journal of the University of Petroleum China, vol. 28, no. 4, pp. 63–66, 2004. View at Google Scholar · View at Scopus
  2. D. Nguyen and S. Rahman, “A Three-Layer Hydraulic Program for Effective Cuttings Transport and Hole Cleaning in Highly Deviated and Horizontal Wells,” in Proceedings of the SPE/IADC Asia Pacific Drilling Technology, Kuala Lumpur, Malaysia, 1996. View at Publisher · View at Google Scholar
  3. R.-C. Cheng and R.-H. Wang, “A three-segment hydraulic model for annular cuttings transport with foam in horizontal drilling,” Journal of Hydrodynamics, vol. 20, no. 1, pp. 67–73, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. Y. Masuda, Q. Doan, M. Oguztoreli et al., “Critical cuttings transport velocity in inclined annulus: experimental studies and numerical simulation,” in Proceedings of the SPE/CIM International Conference on Horizontal Well Technology, Calgary, Alberta, Canada, 2000. View at Publisher · View at Google Scholar
  5. X. Song, Z. Guan, and S. Chen, “Mechanics Model of Critical Annular Velocity for Cuttings Transport in Deviated Well,” Journal of China University of Petroleum, vol. 33, no. 1, pp. 53–63, 2009. View at Google Scholar
  6. N. Wei, Y. Meng, G. Li et al., “Cuttings transport models and experimental visualization of underbalanced horizontal drilling,” Mathematical Problems in Engineering, vol. 2013, Article ID 764782, 6 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. A. Ramadan, P. Skalle, S. T. Johansen, J. Svein, and A. Saasen, “Mechanistic model for cuttings removal from solid bed in inclined channels,” Journal of Petroleum Science and Engineering, vol. 30, no. 3-4, pp. 129–141, 2001. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Duan, S. Z. Miska, M. Yu, N. E. Takach, R. M. Ahmed, and C. M. Zettner, “Transport of small cuttings in extended-reach drilling,” SPE Drilling & Completion, vol. 23, no. 03, pp. 258–265, 2013. View at Publisher · View at Google Scholar
  9. T. I. Lasen, A. A. Pilehvari, and J. J. Azar, “Development of a new cuttings-transport model for high-angle wellbores including horizontal wells,” SPE Drillings Completion, vol. 122, pp. 129–135, 1997. View at Google Scholar
  10. M. Sorgun, “Simple correlations and analysis of cuttings transport with newtonian and non-newtonian fluids in horizontal and deviated wells,” Journal of Energy Resources Technology, Transactions of the ASME, vol. 135, no. 3, article 032903, 2013. View at Publisher · View at Google Scholar · View at Scopus
  11. H. Guo, X. Jin, and X. Hu, “Research on the solving of nonlinear equation group based on swarm particle optimization,” Computer Engineering and Applications, vol. 15, 2006. View at Google Scholar
  12. D. Wang and Y. Zhou, “Artificial Fish-Swarm Algorithm for Solving Nonlinear Equation,” Application Research of Computers, vol. 24, no. 6, pp. 242–244, 2007. View at Google Scholar
  13. L. W. Yan and S. H. Chen, “Solving nonlinear equations based on an improved genetic algorithm,” Acta Scientiarum Naturalium Universitatis Sunyatseni, vol. 50, no. 1, pp. 9–13, 2011. View at Google Scholar · View at MathSciNet
  14. L. L. Wu, Z. R. Wang, and C. J. Zhu, “Evolutionary strategy based on a simulated annealing algorithm to solve a system of nonlinear equations,” Journal of Hefei University of Technology, vol. 31, no. 2, pp. 301–304, 2008. View at Google Scholar · View at MathSciNet
  15. Y. Luo, D. Yuan, and G. Tang, “Hybrid genetic algorithm for solving systems of nonlinear equations,” Chinese Journal of Computation Mechanics, vol. 22, no. 1, pp. 109–114, 2005. View at Google Scholar
  16. Q. Tian, Z. Gu, and X. Zhou, “Solving systems of nonlinear equations with hybrid genetic algorithm,” Computer Technology And Development, vol. 173, pp. 10–12, 2007. View at Google Scholar
  17. A. Ouyang, L. Liu, and G. Yue, “Hybrid particle swarm optimization for solving systems of nonlinear functions,” Computer Engineering And Applications, vol. 47, no. 9, pp. 33–36, 2011. View at Google Scholar
  18. B. Zhang and H. Zhang, “Ant colony algorithm for solving nonlinear equations,” Industrial Control Computer, vol. 26, no. 1, pp. 63-64, 2013. View at Google Scholar
  19. X. Wu, Solving TSP Problem and Systems of Nonlinear Equations with Ant Colony Algorithm , Masters Thesis [Master, thesis], Shanxi Normal University, 2008.
  20. A. A. Gavignet and I. J. Sobey, “Model aids cuttings transport prediction,” JPT, Journal of Petroleum Technology, vol. 41, no. 9, pp. 916–15417, 1989. View at Publisher · View at Google Scholar · View at Scopus
  21. A. Rashno, B. Nazari, S. Sadri, and M. Saraee, “Effective pixel classification of Mars images based on ant colony optimization feature selection and extreme learning machine,” Neurocomputing, vol. 226, pp. 66–79, 2017. View at Publisher · View at Google Scholar
  22. F. Zhao, Z. Yao, J. Luan, and X. Song, “A novel fused optimization algorithm of genetic algorithm and ant colony optimization,” Mathematical Problems in Engineering, vol. 2016, Article ID 2167413, 10 pages, 2016. View at Publisher · View at Google Scholar · View at Scopus
  23. H. Ismkhan, “Effective heuristics for ant colony optimization to handle large-scale problems,” Swarm and Evolutionary Computation, vol. 32, pp. 140–149, 2017. View at Publisher · View at Google Scholar · View at Scopus
  24. M. Maboudi, J. Amini, M. Hahn, and M. Saati, “Object-based road extraction from satellite images using ant colony optimization,” International Journal of Remote Sensing, vol. 38, no. 1, pp. 179–198, 2017. View at Publisher · View at Google Scholar · View at Scopus
  25. S. Bououden, M. Chadli, and H. R. Karimi, “An ant colony optimization-based fuzzy predictive control approach for nonlinear processes,” Information Sciences. An International Journal, vol. 299, pp. 143–158, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. S. Chatterjee and S. Das, “Ant colony optimization based enhanced dynamic source routing algorithm for mobile ad-hoc network,” Information Sciences. An International Journal, vol. 295, pp. 67–90, 2015. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  27. O. Castillo, H. Neyoy, J. Soria, P. Melin, and F. Valdez, “A new approach for dynamic fuzzy logic parameter tuning in ant colony optimization and its application in fuzzy control of a mobile robot,” Applied Soft Computing Journal, vol. 28, pp. 150–159, 2015. View at Publisher · View at Google Scholar · View at Scopus
  28. B. Fonooni, A. Jevtić, T. Hellström, and L.-E. Janlert, “Applying ant colony optimization algorithms for high-level behavior learning and reproduction from demonstrations,” Robotics and Autonomous Systems, vol. 65, pp. 24–39, 2015. View at Publisher · View at Google Scholar · View at Scopus
  29. Q. Ni, H. Xing, Z. Zhang, and alet., “Ant colony algorithm and its applications: review and progress,” in Computer applications and software, vol. 25, pp. 12–16, 6 edition, 2008. View at Google Scholar
  30. Y. Hajizadeh, M. A. Christie, and V. Demyanov, “Ant Colony Optimization Algorithm for History Matching,” in Proceedings of the EUROPEC/EAGE Conference and Exhibition, Amsterdam, The Netherlands, 2009. View at Publisher · View at Google Scholar
  31. J. Yang, Research of Ant Colony Algorithm and Its Applications , [Ph.D. thesis], Zhejiang University, Hangzhou, 2007.
  32. H. Duan, D. Wang, and X. Yu, “Ant colony algorithm: survey and prospect,” Engieering science, vol. 9, no. 2, pp. 98–102, 2007. View at Google Scholar