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
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