مدل‌سازی کشش بین‎سطحی سیستم آب شور/ نفت خام/ سورفکتانت آنیونی با روش برنامه‎ریزی ژنتیک

نوع مقاله: مقاله پژوهشی

نویسندگان

دانشکده‌ مهندسی شیمی، نفت و گاز، دانشگاه علم و صنعت، تهران، ایران

چکیده

مواد فعال‎سطحی به‎عنوان مهم‌ترین ترکیبات شیمیایی در فرآیند ازدیاد برداشت شیمیایی، می‏‏توانند با کاهش کشش بین‎سطحی میان محلول آبی تزریقی و نفت مخزن، ضمن تغییر ترشوندگی محیط متخلخل، مقادیر قابل‌توجهی از نفت باقی‎مانده در مخزن را که به‌صورت پراکنده درون حفره‌ها و گلوگاه‌ها به‎دام افتاده‏اند، آزاد کنند و به‎سمت چاه تولیدی هدایت نمایند. با توجه به نقش مواد فعال‎سطحی، لازم است روش‏هایی برای پیش‌بینی عملکرد آن‌ها در فرآیند ازدیاد برداشت ارائه شود. در پروژه‌ی حاضر، مجموعه‌ای از دو مدل‌ ریاضی داده‌محور برای تخمین‏‏ کشش بین‎سطحی سیستم آب‌شور/ نفت خام/ سورفکتانت آنیونی ساخته شده‌اند که در تولید آن‌ها از 598 داده تجربی استفاده شده است. برای ایجاد همبستگی میان متغیرهای مستقل و تابع هدف، از روش برنامه‌ریزی ژنتیک به‎عنوان یکی از قوی‌ترین ابزارهای مدل‌سازی بهره گرفته شده است. مجذور ضریب همبستگی (R2) روابط ایجاد شده برابر با 946/0 و 9387/0 و جذر میانگین مربعات خطا (RMSD) برای این روابط، برابر با mN/m 4439/3 و mN/m 3261/3 است. سادگی و تخمین‌های مناسب، از ویژگی‌های روابط تولید شده است.
 
 
 
 
 

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Modelling Interfacial Tension of Crude Oil-Brine-Anionic Surfactant Using a Genetic Programming Approach

نویسندگان [English]

  • Danial Abooali
  • Shahrokh Shahhosseini
  • Mohammad Amin Sobati
  • Mehdi Assareh
School of Chemical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran
چکیده [English]

Surface active agents (surfactants) as the most important chemicals to enhance oil recovery (EOR) can reduce interfacial tension between the injected aqueous solution and the oil in a reservoir. They change wettability of the porous media to release and move the remaining oil trapped in the pores and throats towards the well. According to the important roles of the surfactants, it is necessary to predict their performance for EOR process. In this research, two data-based mathematical models were developed to estimate interfacial tension of the oil, salty water and anionic surfactant system using 598 experimental data. To obtain the correlations between the independent variables and the objective function, genetic programing has been applied. Squared correlation coefficient (R2) of the models is 0.946 and 0.9387; moreover, root-mean-square deviation (RMSD) of the models is 3.4439 mN/m and 3.3261 mN/m respectively. Simplicity and acceptable estimation are particular features of the models.
 

کلیدواژه‌ها [English]

  • Interfacial Tension
  • Anionic Surfactant
  • Crude Oil
  • Salty Water
  • Mathematical Model
  • Genetic Programing

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