Viscosity of liquid hydrocarbons, mixtures and petroleum cuts, as a function of pressure and temperature

Kanti, M.; Zhou, Honggang; Ye, S.; Boned, Christian; Lagourette, B.; Saint-Guirons, H.; Xans, P.; Montel, François

doi:10.1021/j100346a097

Cited by 59 publications

(53 citation statements)

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“…For pure carbon dioxide, the experimental viscosity values between 303.15 and 353.15 K and from 10 to 60 MPa were taken from a previous work of Pensado et al 17 For PEC5, PEC7, PEC9, and PEB8 the g values already measured between 303.15 and 353.15 K and from 0.1 to 60 MPa were used. 22,23 The models considered range from the simple classical mixing laws by Grunberg and Nissan 31 and Katti and Chaudhri 32 through empirical general correlations, such as the self-referencing model, 63 to recent approaches with a physical and theoretical background, such as the hard-sphere scheme 36,37,39 and the free-volume model.…”

Section: Viscosity Modelingmentioning

confidence: 99%

“…Self-referencing method. This method was developed by Kanti et al 63 in order to model the viscous behavior of petroleum cuts that have a complex composition which is difficult to characterize. For this kind of fluid, it is difficult to use equations based on physical properties such as the molar mass, critical parameters or acentric factors, as well as on the exact composition of the mixture.…”

Section: -35mentioning

confidence: 99%

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High‐pressure viscosity and density of carbon dioxide + pentaerythritol ester mixtures: Measurements and modeling

et al. 2008

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This article reports densities and viscosities up to 60 MPa and from 303.15 to 353.15 K on two binary mixtures of CO 2 and lubricant pentaerythritol tetra-2-ethylhexanoate with 7.8% and 14.4% mass fraction of lubricant. Because CO 2 and the lubricant are not in the same phase at atmospheric pressure and room temperature, a specially-designed vibrating-wire apparatus has been used. The experimental data, together with our previous data for six mixtures of CO 2 and three polyolesters, have been used to test the predictive and correlation ability of several models: simple mixing laws, the self-referencing method, and the hard-sphere and free volume models. In general, it is not possible to predict the viscosity with deviations smaller than 10%. The hard-sphere model and the self-referencing model are the more adequate to represent the viscosity of these mixtures. Most of the models studied underestimate the viscosities over the investigated (T,p) range.

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Section: Viscosity Modelingmentioning

confidence: 99%

Section: -35mentioning

confidence: 99%

High‐pressure viscosity and density of carbon dioxide + pentaerythritol ester mixtures: Measurements and modeling

et al. 2008

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“…First of all, a compositional model for predicting the viscosity of petroleum fluids as a function of temperature and pressure is presented by Werner et al (1998). It is based on the original model, termed the Self-Reference Model, developed by Kanti et al (1989). This model …”

Section: The Transport Properties Prediction (Trapp) Program Of Ely Amentioning

confidence: 99%

Phase Behavior, Solid Organic Precipitation, and Mobility Characterization Studies in Support of Enhanced Heavy Oil Recovery on the Alaska North Slope

Patil¹,

Dandekar²,

Khataniar³

2008

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The medium-heavy oil (viscous oil) resources in the Alaska North Slope are estimated at 20 to 25 billion barrels. These oils are viscous, flow sluggishly in the formations, and are difficult to recover. Recovery of this viscous oil requires carefully designed enhanced oil recovery processes. Success of these recovery processes is critically dependent on accurate knowledge of the phase behavior and fluid properties, especially viscosity, of these oils under variety of pressure and temperature conditions. This project focused on predicting phase behavior and viscosity of viscous oils using equations of state and semi-empirical correlations.An experimental study was conducted to quantify the phase behavior and physical properties of viscous oils from the Alaska North Slope oil field. The oil samples were compositionally characterized by the simulated distillation technique. Constant composition expansion and differential liberation tests were conducted on viscous oil samples. Experiment results for phase behavior and reservoir fluid properties were used to tune the Peng-Robinson equation of state and predict the phase behavior accurately. A comprehensive literature search was carried out to compile available compositional viscosity models and their modifications, for application to heavy or viscous oils. With the help of meticulously amassed new medium-heavy oil viscosity data from experiments, a comparative study was conducted to evaluate the potential of various models. The widely used corresponding state viscosity model predictions deteriorate when applied to heavy oil systems. Hence, a semi-empirical approach (the Lindeloff model) was adopted for modeling the viscosity behavior. Based on the analysis, appropriate adjustments have been suggested: the major one is the division of the pressure-viscosity profile into three distinct regions. New modifications have improved the overall fit, including the saturated viscosities at low pressures. However, with the limited amount of geographically diverse data, it is not possible to develop a comprehensive predictive model. Based on the comprehensive phase behavior analysis of Alaska North Slope crude oil, a reservoir simulation study was carried out to evaluate the performance of a gas injection enhanced oil recovery technique for the West Sak reservoir. It was found that a definite increase in viscous oil production can be obtained by selecting the proper injectant gas and by optimizing reservoir operating parameters. A comparative analysis is provided, which helps in the decision-making process.iv

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“…On peut citer les travaux de Dymond et Oye (1994) [7] pour la température et Tanaka et al (1991) [8], ainsi que Assael et al (1991) [9] pour la pression. Des prédictions simultanées de l'effet de la température et de la pression ont été envisagées par Comunas et al (2001) [10] et Kanti et al (1989) [11], permettant ainsi de combiner les lois d'Andrade et de Tait. En effet, ces modèles utilisent en entrée de la loi en température la viscosité du brut de stockage, et une équation de type Tait pour calculer l'effet de la pression sur la viscosité de fractions liquides.…”

Section: Modèles Spécifiquesunclassified

“…Un autre modèle, W3BH [26,27] développé dans la thèse de Werner (1996) [28], combine la loi de mélange de Grunberg et Nissan (1949) [29] et le modèle de Kanti et al (1989) [11]. Comme Elsharkawy, ce modèle W3BH permet de prédire la viscosité d'un fluide en fonction de sa composition, sa pression et sa température.…”

Section: Modèles Compositionnelsunclassified

Modélisation de la viscosité des fluides de gisement : Apport de la PLS bootstrap et des réseaux de neurones

Gayon¹,

Pina

Ahmed

et al. 2008

Oil & Gas Science and Technology - Rev. IFP

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Résumé -La régression linéaire Partial Least Squares (PLS) avec ré-échantillonnage par bootstrap et la régression non-linéaire par réseaux de neurones ont été utilisées pour construire des modèles de prédic-tion de la viscosité de fluides de gisement en fonction de leur composition, de la température et de la pression. Les modèles statistiques résultants permettent de prédire des valeurs de viscosité s'étendant de 0,21 cP à 10000 cP. Abstract

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Viscosity of liquid hydrocarbons, mixtures and petroleum cuts, as a function of pressure and temperature

Cited by 59 publications

References 0 publications

High‐pressure viscosity and density of carbon dioxide + pentaerythritol ester mixtures: Measurements and modeling

High‐pressure viscosity and density of carbon dioxide + pentaerythritol ester mixtures: Measurements and modeling

Phase Behavior, Solid Organic Precipitation, and Mobility Characterization Studies in Support of Enhanced Heavy Oil Recovery on the Alaska North Slope

Modélisation de la viscosité des fluides de gisement : Apport de la PLS bootstrap et des réseaux de neurones

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