Optimization of Hole Cleaning in Deviated Wells Using Metaheuristic Algorithms

Document Type : Research Paper


Department of Petroleum, Mining and Material Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran



Field experience shows that the cutting transportation and hole-cleaning phenomena are essential during the drilling phase. Particularly in directional drilling, when the accumulation of cutting has caused some drilling problems such as drill string sticking, formation failure, slow rate of penetration, drill bit abrasion, and the like. Through the study, a novel method for efficient hole cleaning, considering different parameters such as flow rate, the drill bit nozzles’ flow area, the consistency and flow behavior indices in the same time using PSO and ACO algorithms were implemented. Moreover, Power Law has been considered for the fluid rheology model. Based on this, the research parameter shows that the PSO algorithm is much more accurate than the ACO algorithm, improving objective function by 50% and 4%, respectively. The performance of each algorithm was evaluated, and the results show that hole cleaning has been significantly improved. The flow rate and the bit nozzle size, which play key roles, were selected as optimization variables. Effective parameters on hole cleaning were evaluated, and the results before and after optimization showed a significant improvement in the model. The PSO and ACO algorithms have been coded in MATLAB software, and the results are compared to the results of the ant colony. The amount of PV and YP has an inverse effect on the increment of minimum velocity required for cutting transport. Various model analyses reveal that the PSO algorithm is more accurate and robust than the Ant colony algorithm.


  1. Ogunrinde J O, Dosunmu A (2012) Hydraulic optimization for efficient hole cleaning in deviated and horizontal wells, paper SPE presented at the 2012 SPE Nigerian Annual Intenational, 6-8. ##
  2. Lim K M, Chukwu G A (1996) Bit Hydraulics analysis for efficient hole cleaning, Paper presented at the SPE Western Regional Meeting, Anchorage, Alaska. ##
  3. Bernt S A (2010) Modern well design, CRC Press; 2nd edition. ##
  4. Mohammadsalehi M, Malekzadeh N (2012) Optimization of hole cleaning and cutting removal in vertical, deviated and horizontal wells, Paper Presented at the International Petroleum Technology Conference held in Bangkok, Thailand, 7–9. ##
  5. Cayeux E, Leulsegend A, Kluge R, Haga J (2016) Use of a transient cutting transport model in the planning, monitoring and post analysis of complex drilling operation in the North Sea, In IADC/SPE Drilling Conference and Exhibition. OnePetro. ##
  6. Heitmann N, Molero R, Molero R , Graterol W , Ouali Y, Chamat Burgos E , Cisneros A (2014) Novel integrated hole-cleaning concept reduces well construction by 3 rig days, Paper presented at the IADC/SPE Asia Pacific Drilling Technology Conference, Bangkok, Thailand. ##
  7. Zhang F, Miska S, Yu M, Ozbayoglu E, Takach N, Osgouei R E (2015) Is well clean enough? a fast approach to estimate hole cleaning for directional drilling, Paper presented at the SPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition, The Woodlands. ##
  8. Thompson J, Wilkes J, Marland C, Martin A, Bindl B, Brunneder M (2015) Hole-cleaning optimization: a case history from three high-angle wells in Austria, Paper Presented at the SPE Western Regional Meeting, Garden Grove, California, USA. ##
  9. Guan Z C, Liu Y M, Liu Y W, Xu Y Q (2016) Hole cleaning optimization of horizontal wells with the multidimensional ant colony algorithm, Journal of Natural Gas Science and Engineering, 28:347-355. ##
  10. Zhou F, Pu C (1998) Study on cuttings bed height prediction in eccentric annulus of horizontal well, Petrolum Drill Technology. ##
  11. Selvi V, Umarani R (2010) Comparative analysis of ant colony and particle swarm optimization techniques, International Journal of Computer Applications, 5:1-6. ##
  12. Abdulkader M S, Gajpal Y, ElMekkawy Y T (2015) Hybridized ant colony algorithm for the multi–Compartment Vehicle Routing Problem, Applied Soft Computing, 37: 196-203. ##
  13. Benhala B, Ahaitouf A, Mechaqrane A (2012) Multi objective optimization of an operational amplifier by the ant colony optimization algorithm, Electrical and Electronic Engineering, 2, 4: 230-235. ##
  14. Jovanovic R, Tuba M, Voß S (2016) An ant colony optimization algorithm for partitioning graphs with supply and demand, Applied Soft Computing, 41: 317-330. ##
  15. Dosumnu P A, Cosmas O, Orun C, Anyanwu C, Ekeinde E (2015) Optimization of hole cleaning using dynamic real-time cuttings monitoring tools, Paper presented at the SPE Nigeria Annual International Conference and Exhibition, Lagos, Nigeria. ##
  16. Purian F Kh, Farokhoi F, Nadooshan R S (2013) Comparing the performance of genetic algorithm and ant colony optimization algorithm for mobile robot path planning in the dynamic environments with different complexities, Journal of Academic and Applied Studies, 3. ##
  17. Puymbroeck LV (2013) Increasing drilling performance using hydro-mechanical hole cleaning devices, Paper Presented at the SPE Unconventional Gas Conference and Exhibition, Muscat, Oman. ##
  18. Kaveh A, Talatahari S (2009) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures, Computer and Sructures, 87, 5-6: 267-283. ##
  19. Mohanty B, Panda S (2013) Hybrid BFOA-PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems, Applied Soft Computing, 13, 12: 4718-4730. ##
  20. Assareh E, Behrang MA, Assari M R, Ghanbarzadeh A (2010) Application of PSO and GA Techniques on demand estimation of oil in Iran, Energy, 35, 12: 5223-5229. ##
  21. Clerc M (2006) Stagnation analysis in particle swarm optimization or what happens when nothing happens, Technical Report CSM-460, Department of Computer Science, University of Essex, Edited by Riccardo Poli. ##
  22. Karimi Nasab M, Modarres M, Seyedhosseini S M (2015) A self-adaptive PSO for joint lot sizing and job shop scheduling with compressible process times, Applied Soft Computing, 27: 137-147. ##
  23. Tsai C Y, Chen C J (2015) A PSO-AB classifier for solving sequence classification problems, Applied Soft Computing, 27: 11-27. ##
  24. Nwagu C, Awobadejo T, Gaskin K (2014) Application of mechanical cleaning device: hole cleaning tubulars, to Improve Hole Cleaning, Paper presented at the SPE Nigeria Annual International Conference and Exhibition, Lagos, Nigeria. ##
  25. Kennedy J, Eberhardt RC (1995) Particle swarm optimization, In Proceedings of the IEEE International Joint Conference on Neural Networks, IEEE, December, 1942 -1947. ##
  26. Bizhani M, Rodriguez-Corredor F E, Kuru E (2015) Hole cleaning performance of water vs. polymer-based fluids under turbulent flow conditions, Paper Presented at the SPE Canada Heavy Oil Technical Conference, Calgary, Alberta, Canada. ##
  27. Lu Y, Zhou K, Li W, Tian W, Wang X (2014) Research for control parameters optimization of 6-DOF flight simulator based on particle swarm optimization title, In the Twenty-fourth International Ocean and Polar Engineering Conference. OnePetro. ##