Petroleum viscosity modeling using least squares and ANN methods

Stratiev, Dicho; Nenov, Svetoslav; Sotirov, Sotir; Shishkova, Ivelina; Palichev, Georgi Nikolov; Sotirova, Evdokia; Ivanov, Vitaly; Atanassov, Krassimir; Ribagin, Simeon; Angelova, Nora

doi:10.1016/j.petrol.2022.110306

Cited by 9 publications

(3 citation statements)

References 36 publications

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“…The application of the theoretical models is limited to pure hydrocarbons and light crude oils due to the uncertainty with the prediction of critical properties and acentric factor for heavier oils . Recently, ANN techniques have been used to predict the viscosity of crude oils at different temperatures. ,,, However, these ANN techniques are strongly dependent on the reliability and quantity of experimental data and fail to give directly a mathematical expression to describe the viscosity–temperature relationship.…”

Section: Temperature-dependent Viscosity Modelsmentioning

confidence: 99%

“…15 Recently, ANN techniques have been used to predict the viscosity of crude oils at different temperatures. 8,10,12,16 However, these ANN techniques are strongly dependent on the reliability and quantity of experimental data and fail to give directly a mathematical expression to describe the viscosity−temperature relationship. Many empirical temperature-dependent viscosity models have been developed and widely applied to predict crude oil viscosity, as they directly give the temperature-dependent viscosity expression and are easy to be used, especially for those with fewer parameters in the models.…”

Section: Temperature-dependent Viscosity Modelsmentioning

confidence: 99%

“…Consequently, it is necessary to develop a temperature-dependent viscosity model for accurately predicting the viscosity of various crude oils at different temperatures. Dozens of the temperature-dependent viscosity models for crude oils, or their fractions, have been reported by different researchers in the literature, which have been briefly reviewed by others. ,− However, as shown in section , these temperature-dependent viscosity models are quite different. Many of them may have some limitation, as they were developed on the basis of researchers’ own set of experimental data, data from the literature for some crude oils, and/or at a relatively narrow range of temperature. , The extrapolation of these models to other crude oils or other temperature ranges may result in low accuracy of the predictions.…”

Section: Introductionmentioning

confidence: 99%

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Development of a New Temperature-Dependent Viscosity Model for Crude Oils

Bouresli

Albazzaz

et al. 2023

Ind. Eng. Chem. Res.

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The objective of this study is to develop a more accurate model for predicting the dynamic viscosity of a wide range of crude oils at different temperatures. The dynamic viscosities of four Kuwaiti crude oils and a Maya heavy crude oil with an API gravity range of 11.3−26.5 were measured over a temperature range of 25−150 °C, and then the obtained data were used to compare and evaluate the six major empirical temperature-dependent viscosity models reported in the literature. According to the temperature-viscosity correlation, a new empirical temperaturedependent viscosity model was first proposed for crude oils. The linear regression analysis and the statistic deviation analysis were conducted in comparison of the new temperature-dependent viscosity model with the six existing models. Deviation of the various models for the five different crude oils was calculated and discussed in detail. The results show that the new model displays the best correlation performance, giving the smallest average relative deviation of 3.0%, in comparison with the six existing models.

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