مدل‌سازی و شبیه‌سازی عملکرد دستگاه لوله قلمی با شبکه‌های عصبی جهت تعیین حداقل فشار امتزاجی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشگاه علم و صنعت ایران، دانشکده مهندسی شیمی

2 آزمایشگاه تحقیقاتی مهندسی فرآیند به کمک کامپیوتر (CAPE)

چکیده

تزریق گاز امتزاجی به مخازن نفت، یکی از موثرترین روش‌های ازدیاد برداشت است. در این فرآیند حداقل فشار امتزاجی، یک پارامتر بسیار مهم و تعیین کننده می‌باشد. در صنعت نفت حداقل فشار امتزاجی معمولا به وسیله آزمایش لوله قلمی به دست می‌آید که یک آزمایش نسبتا پرهزینه و وقت‌گیر است. در این مقاله پس از جمع‌آوری و بررسی نتایج منتشر شده از دستگاه لوله قلمی در داخل و خارج از کشور، یک بانک اطلاعاتی نسبتاً جامعی در این زمینه تشکیل شد. به منظور مدل‌سازی و شبیه‌سازی فرآیند، روش شبکه‌ عصبی به کار گرفته شد. با توجه به تعداد قابل توجه ورودی‌های شبکه و پیچیدگی بین آنها، جهت افزایش راندمان از روش قوانین اختلاط به منظور کاهش تعداد متغیرهای ورودی استفاده شد. در نهایت مدل ارائه شده با توجه به صرفه‌جویی در زمان و هزینه، نسبت به مدل‌های قبلی ارائه شده از خطای کمتر و جامعیت قابل قبولی برخوردار است. ضمن اینکه قدرت پیش‌بینی مدل ارائه شده نیز نسبت به مدل‌های قابل بهتر است.

کلیدواژه‌ها

عنوان مقاله [English]

Determination of Minimum Miscibility Pressure through Modeling and Simulation of Slim Tube Apparatus Performance

نویسندگان [English]

  • Mohammadreza Akbari 1
  • Norollah Kasiri 1
  • Samad Abdi 2
1 Chemical Engineering Department, Iran University of Science and Technology
2 Computer Aided Process Engineering Center, CAPE Iran University of Science and Technology
چکیده [English]

Miscible gas injection is one of the most effective enhanced oil recovery techniques and minimum miscibility pressure (MMP) is an important parameter in miscible gas injection processes. The accurate determination of this parameter is critical for an adequate design of injection equipment and thereby project investment prospects. The objective of the current paper is to develop a new universal artificial neural network model to predict the minimum miscibility pressure of CO2 and hydrocarbon gas flooding. Different MMP correlations and models are proposed regarding the type of injection gas and the mechanism of miscibility respectively based on mathematical and thermodynamic calculations. Almost all of the correlations proposed in the literature either represent condensing/vaporizing mechanisms or give reasonable results only for the limited range of data they are based on. Experimental data from different crude oil reservoirs obtained through slim tube tests are gathered in order to develop a new model in which the mechanisms are included. Mixing rules are used to decrease independent variables. The significance of this model is that MMP can be determined for any composition of oil and gas no matter which mechanism is dominant in achieving miscibility. The comparison of the model results with the reliable data published shows that the results obtained from the new MMP model is more accurate and universal than most of the published models. Finally, a computer program for determining minimum miscibility pressure is presented

کلیدواژه‌ها [English]

  • Minimum Miscibility Pressure (MMP)
  • Miscible Gas Injection
  • neural network
  • Mixing Rules
  • Slim Tube

مراجع

مراجع
[1]. Green D. W., and Whillhite G. P., Enhanced Oil Recovery, Texas, Richardson Publication Ltd. 1998.
[2]. Danesh A., PVT and phase behavior of petroleum reservoir fluid, Amsterdam, Elsevier Publication Ltd. 1998.
[3] Glaso O. “Generalized minimum miscibility pressure correlation”, SPE Journal, Vol. 25, No. 6, pp. 927-934, 1985.
[4]. Kovarik F. S. “A minimum miscibility pressure study using impure CO2 and west Texas oil system” SPE Production Technology Symposium, 11-12 Nov., Lubbock, Texas, 1985.
[5]. Alston R. B. Kokolis G. P. and James C. F. “CO2 minimum miscibility pressure: a correlation for impure CO2 streams”, SPE Journal, Vol. 25, No. 2, pp. 268-274, 1985.
[6]. Sebastian H. M., and Lawrence D. D., “Nitrogen minimum miscibility pressure”, SPE/DOE Enhanced Oil Recovery Symposium, 22-24 April, Tulsa, Oklahoma, 1992.
[7]. Emera M.K., and Sarma H.K., “A Reliable Correlation To Predict the Change in Minimum Miscibility Pressure When CO2 Is Diluted With Other Gases”, SPE Reservoir Evaluation & Engineering, Vol. 9, No. 4, pp. 366-373, 2006.
[8]. Benham A.L., Dowden W.E., and Kunzman W.J., “Miscible Fluid Displacement - Prediction of Miscibility”, AIME, Vol. 219, pp. 229-237, 1960.
[9]. Holm L.W., and Josendal V.A. “Mechanisms of Oil Displacement by Carbon Dioxide”, Journal of Petroleum Technology, Vol. 26, No. 12, pp. 1427-1438, 1974.
[10]. Holm L.W. and Josendal V.A. “Effect of Oil Composition on Miscible-Type Displacement by Carbon Dioxide”, Journal of Petroleum Technology, Vol. 22, No.1, pp. 87-98, 1982.
[11]. Cronquist C., “Carbon Dioxide Dynamic Displacement with Light Reservoir Oils”, Fourth Annual U.S. DOE Symposium, Tulsa, USA, pp.18-23, 1978.
[12]. Lee J.I., Effectiveness of carbon dioxide displacement under miscible and immiscible conditions’ Research Report RR-40, Petroleum Recovery Institute, Calgary, Alberta, 1979.
[13]. Yellig W.F., and Metcalfe R.S., “Determination and prediction of CO2 minimum miscibility pressure”, Journal of Petroleum Technology, Vol. 32, No. 1, pp. 160-168, 1980.
[14]. Johnson J. P., and Pollin J. S. “MEASUREMENT and CORRELATION of CO2 MISCIBILITY PRESSURES”, SPE-DOE Enhanced Oil Recovery Symposium, 5-8 Apr., Tulsa, Oklahoma, 1981.
[15]. Stalkup F.I., “Miscible displacement Monograph series” SPE, Texas, Richardson Publication Ltd., 1998.
[16]. Orr F.M., and Jensen C.M. “Interpretation of Pressure-Composition Phase Diagrams for CO2/Crude-Oil Systems”, SPE Journal, Vol. 24, No. 5, pp. 485-497, 1984.
[17]. Sebastian H.M., Wenger R.S., “Correlation of minimum miscibility pressure for impure CO2 streams”, Journal of Petroleum Technology, Vol. 37, No. 11, pp. 2076-2082, 1985.
[18] Kou L. “Prediction of miscibility for enriched gas drive process” SPE Annual Technical Conference and Exhibition, Las Vegas, Nevada, U.S.A, 1985.
[19]. Firoozabadi A., and Aziz k., “Analysis and correlation of nitrogen and lean gas miscibility pressure”, SPE Reservoir Engineering, Vol. 1, No. 6, pp. 572-582, 1986.
[20]. You L. and Chu M., “A study on the minimum miscibility pressure for miscible flooding system”, J. Pet. Sci. Eng. Vol.8, pp. 315–328. 1993.
[21]. Enick R.M., Holder G.D., and Morsi B.I., “A thermodynamic correlation for the minimum miscibility pressure in CO2 flooding of petroleum reservoir”, SPE Reservoir Engineering, Vol. 3, No. 1, pp. 81-92, 1988.
[22]. Hennsen M.R. “Nitrogen as a low cost replacement for natural gas reinjection offshore”, SPE Gas Technology Symposium, Texas, U.S.A 1988.
[22]. Hudgins D.A., Llave F.M., and Chung F.T, “Nitrogen Miscible Displacement of Light Crude Oil: A Laboratory Study” SPE Reservoir Engineering, Vol. 5, No. 1, pp. 100-106, 1990.
[23]. Olstein Glaso, O. “Miscible Displacement: recovery test with nitrogen”, SPE Reservoir Engineering, Vol. 5, No. 1, pp. 61-68, 1990.
[24]. Dong M. Huang S. and Srivastava R. “Effect of Solution Gas in Oil on CO2 Minimum Miscibility Pressure”, Annual Technical Meeting, Jun 14-18, Calgary, Alberta, Canada, 1999.
[25]. Huang Y. F., Huang G. H., Dong M. Z., and Feng G. M., “Development of an artificial neural network model for predicting minimum miscibility pressure in CO2 flooding”, Journal of Petroleum Science and Engineering, Vol. 37, 83-95. 2003.
[26]. Yuan H., Johns R.T., Egwuenu A.M., and Dindoruk B. “Improves MMP correlation for CO2 floods using analytical gas flooding”, SPE Reservoir Evaluation & Engineering, Vol. 8, No. 5, pp. 418-425, 2004.
[27] Shokir E.M., and Eissa M. “CO2–oil minimum miscibility pressure model for impure and pure CO2 streams”, Journal of Petroleum Science and Engineering, Vol. 58, No. 1, pp. 173-185, 2007.
[28]. Emera M. K., and Sarma H. K., “Use of Genetic Algorithm to Estimate CO2-Oil Minimum Miscibility Pressure-a Key Parameter in Design of CO2 Miscible Flood”, Journal of Petroleum science and Engineering, Vol. 46, No. 1, pp. 37-52. 2004.
[29]. Al-Netaifi S. “Experimental Investigation of CO2 - Miscible Oil Recovery at Different Conditions”, M.Sc. Thesis King Saud University, Riyadh, Saudi Arabia, 2008.
[30]. MMP reports for Iranian α reservoir. N.I.O.C. Report, 2002.
[31]. Haykin S. Neural Networks: A Comprehensive Foundation, 2nd Ed., Prentice Hall, 1998.
[32] Poling B. E., Prausnitz J. M., O’Connell J. P., The Properties of Gases and Liquids, McGraw-Hill, New York, 2004.
[33]. Ahmed T. Hydrocarbon Phase Behavior, Gulf Publishing Company, Houston, 1989.
[34]. Boozarjomehry R.B, Abdolahi F., and Moosavian M.A. “Characterization of Basic Properties of Pure substances and Petroleum Fractions by Neural Network”, Fluid Phase Equlilbria, Vol. 231, No. 2, pp. 188-196, 2005.
[35]. Neural Network MATLAB R2009b Toolbox User Guide.
پژوهش نفت
دوره 22، شماره 71 - شماره پیاپی 71
مهر و آبان 1391
صفحه 28-42

فایل ها

هم رسانی

ارجاع به این مقاله

آمار