بررسی پارامترهای مؤثر بر عملکرد فرآیند نمک‌زدای الکترواستاتیک به‌کمک شبکه عصبی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 آزمایشگاه فرآیندهای جداسازی و نانوفناوری، دانشکده فنی کاسپین، پردیس دانشکده‌های فنی دانشگاه تهران، ایران

2 گروه فناوری‌های تبدیل و بهینه‌سازی، پژوهشکده توسعه فناوری‌های پالایش، پژوهشگاه صنعت نفت، تهران، ایران

3 دانشکده مهندسی شیمی، پردیس دانشکده‌های فنی، دانشگاه تهران، ایران

چکیده

آنچه تحت عنوان نفت خام از چاه‌های نفتی استخراج می‌شود؛ در حقیقت امولسیونی از ذرات ریز آب با اندازه کوچک‌تر از تقریباً μm 100 است که در فاز نفتی پراکنده شده است. این امولسیون که امولسیونی پایدار است؛ در‌صورتی‌که به دو فاز آب و نفت تفکیک نشود؛ موجب بروز مشکلات جدی در فرآیند انتقال و پالایش نفت خام خواهد شد. به منظور جداسازی آب و ترکیبات یونی همراه آن از نفت خام، واحدهای نمک‌زدایی که در آن‌ها از میدان الکتریکی با شدت بالا استفاده می‌شود، مورد استفاده قرار می‌گیرند. بازدهی این واحدها به متغیرهای متعددی وابسته است. در این پژوهش، اثر پارامترهای مختلف بر میزان نمک همراه نفت خروجی یک واحد نمک‌زدا مطالعه شده است. بدین منظور، شبکه عصبی بهینه شده به‌وسیله الگوریتم فاخته مورد استفاده قرار گرفته است. به کمک نتایج شبیه‌سازی، مقادیر بهینه دما، درصد آب تزریقی، افت فشار در شیر اختلاط و غلظت تعلیق‌شکن معین شده است؛ به‌طوری‌که این مقادیر به‌ترتیب برابر با C° 79، 25/3%، bar 85/0 و ppm 90 است. با توجه به اهمیت نوع تعلیق‌شکن، به منظور بررسی اثر آن بر سایر پارامترها، در مطالعه صورت گرفته، از چهار نوع تعلیق‌شکن متفاوت استفاده شده است. نتایج حاصل نشان می‌دهد که افزایش آب و رسوبات همراه نفت و وزن مخصوص نفت خام، بر بازدهی فرآیند نمک‌زدایی تأثیر منفی دارند.
 

کلیدواژه‌ها


عنوان مقاله [English]

Investigation of Parameters Affecting the Performance of Electrostatic Desalting Process Using Neural Network

نویسندگان [English]

  • Hamed Kazemi Golbaghi 1
  • Mehdi Mohammadi 2
  • Seyed Hamed Mousavi 1
  • Moosavian Seyed Mohammad Ali 3
1 Separation Processes and Nanotechnology Lab, Faculty of Caspian, College of Engineering, University of Tehran, Iran
2 Electrocoalescers Research Laboratory, Petroleum Refining and Processing Technology Development Division, Research Institute of Petroleum Industry (RIPI), Tehran, Iran
3 Schoole of Chemical Engineering, College of Engineering, University of Tehran, Iran
چکیده [English]

Dispersed water-in-oil as a stable emulsion causes numerous problems in extraction, transportation and refining of the crude oil. In the most desalting units, high voltage electrical field is utilized to separate water and ionic components from the crude oil. The efficiency of desalting units depends on operational conditions and hence in this study the result of several parameters on salt content of output crude oil in a desalting unit was considered for both theoretical and experimental studies. For this goal, optimized artificial neural network (ANN) using cuckoo optimization algorithm was applied to simulate the process. The optimum temperature, water  injection rate, retention time, differential pressure of mixing valves and injection rate of demulsifier were predicted by the consequences of simulation as the optimum value for each of the parameters was respectively equal to 79 ppm, 3.25%, 8.5 bar and 90 ppm. Then, because of the significant effect of the demulsifiers, the variation of each parameter was evaluated in the presence of four types of demulsifier separately. The results showed that an increase in the basic sediment and water content (BS&W) and specific gravity of crude oil has adverse effects on desalting process efficiency.
 

کلیدواژه‌ها [English]

  • water-in-oil emulsion
  • electrostatic demulsification
  • Artificial Neural Networks
  • Cuckoo optimization
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