کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6632612 | 1424952 | 2018 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The effect of asphaltene content on predicting heavy dead oils viscosity: Experimental and modeling study
ترجمه فارسی عنوان
تأثیر محتوای آسفالتین بر پیش بینی ویسکوزیته روغنهای سنگین: مطالعه تجربی و مدلسازی
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کلمات کلیدی
نفت خام خام، ویسکوزیته سنگین نفت خام، همبستگی تجربی ویسکوزیته، محتوای آسفالتین،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
چکیده انگلیسی
The viscosity of heavy dead oil is one of the most important governing parameters of the fluid flow, either in the porous media or pipelines, so it is of great importance to use accurate empirical correlation to estimate the heavy oil viscosity at various operating temperature. Published heavy oil viscosity correlations resulted in huge errors. The resulted deviations are attributed to the differences in the Asphaltenic content of crude oils and their dependence on operating temperature and density only. Therefore, we need to develop an accurate empirical correlation model that represents the heavy dead crude oil viscosity by adding different effective parameters as Asphaltenic content, oil density at operating temperature and oil molecular weight. In this paper, heavy dead oil empirical correlation has been developed using laboratory data (710 set point) of heavy oil samples that collected from different locations in Egypt. Heavy dead oil viscosity measurements operated at API gravity (22.79â¯>â¯APIâ¯>â¯12.36). Efforts are made to build a best-fit correlation by multiple least-square nonlinear regression analysis to find viscosity as a function of (Asphalten, TOper., API gravity, MWT and ÏOper.temp.). Both statistical and graphical techniques were applied on hundred data point to evaluate this developed empirical correlation with literature ones and experimental data of Egyptian oil samples. The results show that the developed empirical correlation presents better accuracy and performance for predicting the heavy dead oil viscosity than those correlations in literature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuel - Volume 212, 15 January 2018, Pages 405-411
Journal: Fuel - Volume 212, 15 January 2018, Pages 405-411
نویسندگان
E.M. Mansour, S.M. Desouky, M. El Aily, M.E. Helmi,