Development of Viscosity Model for Petroleum Industry Applications

Date
2013-03-07
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Abstract
Heavy oil and bitumen are challenging to produce and process due to their very high viscosity, but their viscosity can be reduced either by heating or dilution with a solvent. Given the key role of viscosity, an accurate viscosity model suitable for use with reservoir and process simulators is essential. While there are several viscosity models for natural gases and conventional oils, a compositional model applicable to heavy petroleum and diluents is lacking. The objective of this thesis is to develop a general compositional viscosity model that is applicable to natural gas mixtures, conventional crudes oils, heavy petroleum fluids, and their mixtures with solvents and other crudes. The recently developed Expanded Fluid (EF) viscosity correlation was selected as a suitable compositional viscosity model for petroleum applications. The correlation relates the viscosity of the fluid to its density over a broad range of pressures and temperatures. The other inputs are pressure and the dilute gas viscosity. Each fluid is characterized for the correlation by a set of fluid-specific parameters which are tuned to fit data. First, the applicability of the EF correlation was extended to asymmetric mixtures and liquid mixtures containing dissolved gas components. A new set of mass-fraction based mixing rules was developed to calculate the fluid-specific parameters for mixtures. The EF correlation with the new set of mixing rules predicted the viscosity of over 100 mixtures of hydrocarbon compounds and carbon dioxide with overall average absolute relative deviations (AARD) of less than 10% either with measured densities or densities estimated by Advanced Peng-Robinson equation of state (APR EoS). To improve the viscosity predictions with APR EoS-estimated densities, general correlations were developed for non-zero viscosity binary interaction parameters. The EF correlation was extended to non-hydrocarbon compounds typically encountered in natural gas industry. It was demonstrated that the framework of the correlation is valid for these compounds, except for compounds with strong hydrogen bonding such as water. A temperature dependency was introduced into the correlation for strongly hydrogen bonding compounds. The EF correlation fit the viscosity data of pure non-hydrocarbon compounds with AARDs below 6% and predicted the viscosity of sour and sweet natural gases and aqueous solutions of organic alcohols with overall AARDs less than 9%. An internally consistent estimation method was also developed to calculate the fluid-specific parameters for hydrocarbons when no experimental viscosity data are available. The method correlates the fluid-specific parameters to the molecular weight and specific gravity. The method was evaluated against viscosity data of over 250 pure hydrocarbon compounds and petroleum distillations cuts. The EF correlation predictions were found to be within the same order of magnitude of the measurements with an overall AARD of 31%. A methodology was then proposed to apply the EF viscosity correlation to crude oils characterized as mixtures of the defined components and pseudo-components. The above estimation methods are used to calculate the fluid-specific parameters for pseudo-components. Guidelines are provided for tuning of the correlation to available viscosity data, calculating the dilute gas viscosities, and improving the densities calculated with the Peng-Robinson EoS. The viscosities of over 10 dead and live crude oils and bitumen were predicted within a factor of 3 of the measured values using the measured density of the oils as the input. It was shown that single parameter tuning of the model improved the viscosity prediction to within 30% of the measured values. Finally, the performance of the EF correlation was evaluated for diluted heavy oils and bitumens. The required density and viscosity data were collected for over 20 diluted dead and live bitumen mixtures using an in-house capillary viscometer also equipped with an in-line density-meter at temperatures and pressures up to 175 °C and 10 MPa. The predictions of the correlation were found within the same order of magnitude of the measured values with overall AARDs less than 20%. It was shown that the predictions of the correlation with generalized non-zero interaction parameters for the solvent-oil pairs were improved to overall AARDs less than 10%.
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Engineering--Chemical, Engineering--Petroleum
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