Parametric study to develop an empirical correlation for undersaturated crude oil viscosity based on the minimum measured input parameters

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Abstract

In this study, the correlations published in the literature for predicting undersaturated oil viscosity data have been evaluated based on field-measured data collected from PVT reports for different Omani fields. It was found that most of these correlations provide good prediction for undersaturated Omani crude oil viscosity with Bergman and Sutton [1] being the best. Then, evaluation analysis was carried out using both calculated bubble point pressure and bubble point oil viscosity data and adopting published correlations for these two parameters. It was found that the calculated bubble point pressure have insignificant effect on the predicted viscosity; therefore it was indicated that the correlations published by Standing [2] and Al-Shammasi [3] can be used to predict bubble point pressure in case of lack of these data. On the other hand, the calculated bubble point oil viscosity was found to have a significant effect on the calculated undersaturated oil viscosity. Therefore, a new correlation for this parameter was developed by applying the genetic algorithm optimization methodology on the collected experimental data. The validation test indicated that the correlation developed in this study for bubble point oil viscosity outperformed all the correlations available in the literature. Hossain et al. [4] correlation proved to have the best prediction for the undersaturated oil viscosity, while the Standing [2] correlation is recommended for predicting the bubble point pressure. On the other hand, the newly developed correlation gave the best performance for predicting the bubble point oil viscosity.

Original languageEnglish
Pages (from-to)111-119
Number of pages9
JournalFuel
Volume119
DOIs
Publication statusPublished - Mar 1 2014

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Petroleum
Crude oil
Viscosity
Oils
Genetic algorithms

Keywords

  • Bubble point pressure
  • Omani crude oil
  • Undersaturated
  • Viscosity

ASJC Scopus subject areas

  • Fuel Technology
  • Energy Engineering and Power Technology
  • Chemical Engineering(all)
  • Organic Chemistry

Cite this

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title = "Parametric study to develop an empirical correlation for undersaturated crude oil viscosity based on the minimum measured input parameters",
abstract = "In this study, the correlations published in the literature for predicting undersaturated oil viscosity data have been evaluated based on field-measured data collected from PVT reports for different Omani fields. It was found that most of these correlations provide good prediction for undersaturated Omani crude oil viscosity with Bergman and Sutton [1] being the best. Then, evaluation analysis was carried out using both calculated bubble point pressure and bubble point oil viscosity data and adopting published correlations for these two parameters. It was found that the calculated bubble point pressure have insignificant effect on the predicted viscosity; therefore it was indicated that the correlations published by Standing [2] and Al-Shammasi [3] can be used to predict bubble point pressure in case of lack of these data. On the other hand, the calculated bubble point oil viscosity was found to have a significant effect on the calculated undersaturated oil viscosity. Therefore, a new correlation for this parameter was developed by applying the genetic algorithm optimization methodology on the collected experimental data. The validation test indicated that the correlation developed in this study for bubble point oil viscosity outperformed all the correlations available in the literature. Hossain et al. [4] correlation proved to have the best prediction for the undersaturated oil viscosity, while the Standing [2] correlation is recommended for predicting the bubble point pressure. On the other hand, the newly developed correlation gave the best performance for predicting the bubble point oil viscosity.",
keywords = "Bubble point pressure, Omani crude oil, Undersaturated, Viscosity",
author = "Majda Al-Balushi and Mjalli, {Farouq S.} and Talal Al-Wahaibi and Yahya Al-Wahaibi and Al-Hashmi, {Abdul Aziz}",
year = "2014",
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doi = "10.1016/j.fuel.2013.11.044",
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T1 - Parametric study to develop an empirical correlation for undersaturated crude oil viscosity based on the minimum measured input parameters

AU - Al-Balushi, Majda

AU - Mjalli, Farouq S.

AU - Al-Wahaibi, Talal

AU - Al-Wahaibi, Yahya

AU - Al-Hashmi, Abdul Aziz

PY - 2014/3/1

Y1 - 2014/3/1

N2 - In this study, the correlations published in the literature for predicting undersaturated oil viscosity data have been evaluated based on field-measured data collected from PVT reports for different Omani fields. It was found that most of these correlations provide good prediction for undersaturated Omani crude oil viscosity with Bergman and Sutton [1] being the best. Then, evaluation analysis was carried out using both calculated bubble point pressure and bubble point oil viscosity data and adopting published correlations for these two parameters. It was found that the calculated bubble point pressure have insignificant effect on the predicted viscosity; therefore it was indicated that the correlations published by Standing [2] and Al-Shammasi [3] can be used to predict bubble point pressure in case of lack of these data. On the other hand, the calculated bubble point oil viscosity was found to have a significant effect on the calculated undersaturated oil viscosity. Therefore, a new correlation for this parameter was developed by applying the genetic algorithm optimization methodology on the collected experimental data. The validation test indicated that the correlation developed in this study for bubble point oil viscosity outperformed all the correlations available in the literature. Hossain et al. [4] correlation proved to have the best prediction for the undersaturated oil viscosity, while the Standing [2] correlation is recommended for predicting the bubble point pressure. On the other hand, the newly developed correlation gave the best performance for predicting the bubble point oil viscosity.

AB - In this study, the correlations published in the literature for predicting undersaturated oil viscosity data have been evaluated based on field-measured data collected from PVT reports for different Omani fields. It was found that most of these correlations provide good prediction for undersaturated Omani crude oil viscosity with Bergman and Sutton [1] being the best. Then, evaluation analysis was carried out using both calculated bubble point pressure and bubble point oil viscosity data and adopting published correlations for these two parameters. It was found that the calculated bubble point pressure have insignificant effect on the predicted viscosity; therefore it was indicated that the correlations published by Standing [2] and Al-Shammasi [3] can be used to predict bubble point pressure in case of lack of these data. On the other hand, the calculated bubble point oil viscosity was found to have a significant effect on the calculated undersaturated oil viscosity. Therefore, a new correlation for this parameter was developed by applying the genetic algorithm optimization methodology on the collected experimental data. The validation test indicated that the correlation developed in this study for bubble point oil viscosity outperformed all the correlations available in the literature. Hossain et al. [4] correlation proved to have the best prediction for the undersaturated oil viscosity, while the Standing [2] correlation is recommended for predicting the bubble point pressure. On the other hand, the newly developed correlation gave the best performance for predicting the bubble point oil viscosity.

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