Crude oil viscosity is an important physical property that controls and influences the flow of oil through porous media and pipelines. Hence, it is the basis of many reservoir engineering and production system calculations. In the crude oil recovery and processing, viscosity is significant parameter as a large amount of time and money are spent in experimental measurements of viscosity. This necessitates the development of reliable viscosity models capable of predicting crude oil viscosity and eliminates the expensive and cumbersome experimental measurements.
This paper presents new compositional models for estimating crude oil viscosity. The new models use fluid composition, temperature and pressure to predict oil viscosity. The models were derived from viscosity measurements of several crudes from the Middle East, North Sea and others. Accuracy of the proposed models has been compared to that for several empirical correlations, corresponding state models, and equation of state based viscosity models. The comparison shows the superiority of the new models over the other methods.
The mechanism or theory of gas viscosity has been reasonably well defined by the application of the kinetic theory of the gases. The theory of liquid viscosity is poorly developed due to the intermolecular forces between the molecules, which consist of short-range effects such as repulsion and hydrocarbon bonding, wide range effects such as electrostatic effects, and long-range effects such as attractions. A further complication is the structure and degree of disorder between the molecules. Thus, there is no widely accepted simple theoretical method to calculate viscosity of liquids1.
Petroleum crude oils and fractions are typically complex mixtures, and the physical and chemical properties vary considerably depending on the composition of the constituents. For instance, the viscosity of a crude oil or a fraction composed mostly of aromatics might have quite different temperature dependence than that composed mostly of saturates. Useful viscosity prediction methods are most conveniently based on parameters such as boiling temperatures and specific gravities that are commonly used to characterize each fraction2. The relatively successful viscosity models available in the literature can be classified as:
Empirical methods
Corresponding states methods
EOS-based viscosity models
Group contribution methods
Although numerous viscosity correlations for hydrocarbon liquids and gases are available in the literature, there are three main drawbacks in their applications3:
Application range and accuracy are limited.
As the viscosity of liquid phase and gas phase is calculated by using different graphs or correlations, a smooth transition in the near-critical region cannot be achieved.
Density is involved in evaluating the fluid viscosity, and hence, separate density correlation is required.
Recently, the efforts focused toward developing a theoretical viscosity models based on an equation of state (EOS), the major advantages of such models are:
A single model, achieving a smooth transition of liquid/gas viscosity in the near-critical region can describe the viscosity of both gas and liquid phases.
Both high pressure and low-pressure data can be correlated, and density is not involved in evaluating the fluid viscosity.
