استفاده از الگوریتم ازدحام ذرات به‌همراه کنترل‌گر تناسبی در فرآیند بهینه‌سازی مسیر حفاری چاه- مطالعه موردی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 شرکت نفت و گاز پارس، حفاری، تهران، ایران

2 شرکت مشاوران انرژی تهران، ایران

چکیده

یکی از مشکلات هزینه‌بر در مهندسی حفاری، ایجاد ناپایداری در چاه‌های نفت وگاز است. این پدیده تحت تاثیر عواملی همچون آزیموت، زاویه انحراف، تنش درجا، وزن گل و خصوصیات مقاومتی سنگ قرار می‌گیرد. از این میان آزیموت، زاویه انحراف و وزن گل از پارامترهای قابل کنترل می‌باشند. در این مقاله الگوریتم جدیدی به منظور تعیین مقدار بهینه فشار گل و نیز مسیر مناسب چاه ارائه شده است. الگوریتم ازدحام ذرات، به‌عنوان موتور بهینه ساز به همراه یک کنترل‌گر تناسبی برای نیل به شرایط بهینه مذکور، مورد استفاده قرار گرفت. زون تسلیم نرمالیزه به‌عنوان شاخص ناپایداری در نظر گرفته شد و به منظور تعیین خطای بین شاخص زون تسلیم نرمالیزه شبیه‌سازی شده و تنظیم شده از یک کنترل‌گر تناسبی استفاده شد. با اعمال الگوریتم ارائه شده در یک چاه انحرافی حفاری شده در جنوب غرب ایران مقدار بهینه آزیموت نزدیک جهت تنش افقی ماکزیمم(°3/358) و مقدار بهینه زاویه انحراف °4/67 به‌دست آمد. فشار گل بهینه متناسب برابر MPa 75/37 می‌باشد.
 

کلیدواژه‌ها


عنوان مقاله [English]

Optimization of Well Trajectory Using Particle Swarm Optimization Algorithm with Association of Proportional Feedbak Control-case Study

نویسندگان [English]

  • Javad Kasravi 1
  • Mohammad Amin Safarzadeh 2
  • Ayoub Vali zadeh 1
1 Pars Oil and Gas Company
2 Tehran Energy Consultants Company
چکیده [English]

One of the important issues in the field of drilling engineering is the instability of oil and gas Wellbore. It is influenced by several factors; such as, azimuth, an inclination angle, in-situ stresses, mud weight, rock strength parameters, and etc. Among these factors, an azimuth angle, an inclination angle and mud weight are controllable. In this paper, a novel algorithm is introduced to obtain optimum Mud Pressure and finding the best well trajectory. Particle Swarm Optimization (PSO) was used as a main optimization engine; moreover, a strategy based on proportional (P) feedback control was applied to archive optimum condition. Normalized Yielded Zone (NYZA) Area was applied as an instability index and the feedback function uses the error between the simulated and set point Normalized Yielded Zone Area. A proposed algorithm is applied in one of directional well located in Ahwaz Oilfield. The results demonstrated that the optimum azimuth angle was near maximum horizontal stress (358.3°), and the optimum inclination angle was 67.4°. In addition, the minimum mud pressure for this trajectory was equal to 37.75 Mpa.
 

کلیدواژه‌ها [English]

  • NYZA
  • Borehole Instability
  • PSO
  • Well Trajectory
  • Optimization

[1] Aslannejad M, Manshad A. and Jalalifar H., “Analysis of vertical, horizontal and deviated wellbores stability,” American Journal of Oil and Chemical Technologies, doi: 10.142266/ajoct18-2, 2013.##

[2]. Chen X. and Haberfield C., “Wellbore stability analysis guidelines for practical well design,” SPE Asia Pacific Oil and Gas Conference, Adelaide, Australia. doi: 10.2118/36972-MS, 1996.##

[3]. Xianjie Y., Seehong O. and James E., “Quantifying the effect of rock strength criteria on minimum drilling mud weight prediction using polyaxial rock strength test data,” Int. J. Geomech., 6(4), pp. 260–268, 2006.##

[4]. Yew CH. and Gefei L., “Pore fluid and wellbore stabilities,” SPE Conference, Beijing, China. doi: 10.2118/22381-MS, 1992.##

[5]. Fuh GH., Whitfill D. L. and Schuh P. R., “Use of borehole stability analysis for successful drilling of high-angle hole,” IADC/SPE drilling conference, Dallas, Texas. doi: 10.2118/17235-MS, 1988.##

[6]. Awal M. R., Khan M. S. and Mohiuddin M. A., “A new approach to borehole trajectory optimization for increased hole stability,” SPE Middle East Oil Show, Bahrain. doi: 10.2118/68092-MS, 2001.##

[7]. Klimentos T., Harouka A., Mtawaa B. and Saner S., “Experimental determination of the biot elastic constant: applications in formation evaluation (sonic porosity, rock strength, earth stresses, and sanding predictions),” SPE Reservoir Evaluation & Engineering. doi: 10.2118/30593-PA, 1998.##

[8]. Zhou S., Hillis R. and Sandiford M., “On the mechanical stability of inclined wellbores,” SPE Drilling & Completion,” doi: 10.2118/28176-PA, 1996.##

[9]. Karstad E. and Aadnoy B. S., “Optimization of borehole stability using 3D stress optimization,” SPE Annual Technical Conference, Dallas, Texas. doi: 10.2118/97149-MS, 2005.##

[10]. Al-Ajmi A., Adel M. and Zimmerman R. W., “A new well path optimization model for increased mechanical borehole stability,” Journal of Petroleum Science and Engineering. doi: 10.1016/j.petrol.2009.05.018, 2009.##

[11]. Zare-Reisabadi M. R., “Determination of optimal well trajectory during drilling and production based on    borehole stability,” International Journal of Rock Mechanics and Mining Sciences 56(0): 77-87, 2012.##

[12]. Hawkes C. D. and Mclellan P. J., “Coupled modeling of borehole instability and multiphase flow for under balanced drilling,” IADC/SPE Drilling Conference, Dallas, Texas. doi: 10.2118/74447-MS, 2002.##

[13]. Goshtasbi K., Elyasi A. and Naeimipour, “A 3D numerical stability analysis of multi-lateral well junctions,” Arab J Geosci. doi: 10.1007/s12517-012-0558-x, 2012.##

[14]. Manshad A., “Analysis of vertical, horizontal and deviated wellbores stability by analytical and numerical methods,” Journal of Petroleum Exploration and Production Technology: 1-11, 2014.##

[15]. Safarzadeh M. A., Motealleh M. and Moghaddasi J., “A novel, streamline-based injection efficiency enhancement method using multi-objective genetic algorithm,” Journal of Petroleum Exploration and Production Technology, Springer Heidelberg, DOI 10.1007/s13202-014-0116-z, 2014.##

[16]. Safarzadeh M. A. and Motahhari S. M., “CO-optimization of carbon dioxide storage and enhanced oil recovery in oil reservoirs using multi objective genetic algorithm (NSGA-II),” Journal of Petroleum Science, Springer Heidelberg, DOI 10.1007/s12182-014-0362, 2014.##

[17]. Hawkes C. D. and McLellan P. J. “Modeling of yielded zone enlargement around a wellbore,” SPE Conference Paper, Montral, Canada1996.##

[18]. McLellan P. J. and Wang Y., “Predicting the effects of pore pressure penetration on the extent of wellbore insta bility: application of a versatile poro-elastoplastic model,” SPE Conference Paper, Delft, Netherlands. doi: 10.2118/28053-MS, 1994.##

[19]. Hawkes C. D. and McLellan P. J., “A new model for predicting time-dependant failure of shales: Theory and Application,” SPE Annual Technical Meeting, Calgary, Alberta. doi: 10.2118/97-131,1997.##

[20]. McLellan P. J., Hawkes C. D. and Read R. S., “Sand production prediction for horizontal wells in gas storage reservoirs,” SPE/CIM International Conference on Horizontal Well Technology, Calgary, Alberta. doi: 10.2118/65510-MS, 2000.##

[21]. Goldberg D. E., “Genetic algorithms in search, optimization and machine learning,” Addison-Wesley, Ontario, 1989.##

[22]. Eberhart R. and Kennedy I., “A new optimizer using particle swarm theory,” Symposium on Micro Machine and Human Science, 4(12), 39-43, 1995.##

[23]. Onwunalu J. E. and Durlofsky L. J., “Application of a particle swarm optimization algorithm for determining optimum well location and type,” Comput. Geosci. Doi: 10.1007/s10596-009-9142-1, 2010.##

[24]. Engelbrecht A., “Computational Intelligence,” John Wiley & Sons, London, 2007.##

[25]. salehi S., “Wellbore Stability analysis in UBD Wells of Iranian fields,” SPE Middle East Oil and Gas Show and Conference. Bahrain, Society of Petroleum Engineers, 2007.##