Viscosity models for mixtures

The shear viscosity (or viscosity, in short) of a fluid is a material property that describes the friction between internal neighboring fluid surfaces (or sheets) flowing with different fluid velocities. This friction is the effect of (linear) momentum exchange caused by molecules with sufficient energy to move (or "to jump") between these fluid sheets due to fluctuations in their motion. The viscosity is not a material constant, but a material property that depends on temperature, pressure, fluid mixture composition, local velocity variations. This functional relationship is described by a mathematical viscosity model called a constitutive equation which is usually far more complex than the defining equation of shear viscosity. One such complicating feature is the relation between the viscosity model for a pure fluid and the model for a fluid mixture which is called mixing rules. When scientists and engineers use new arguments or theories to develop a new viscosity model, instead of improving the reigning model, it may lead to the first model in a new class of models. This article will display one or two representative models for different classes of viscosity models, and these classes are:

  • Elementary kinetic theory and simple empirical models[1][2][3] - viscosity for dilute gas with nearly spherical molecules
  • Power series[2][3] - simplest approach after dilute gas
  • Equation of state analogy[3] between PVT and TP
  • Corresponding state[2][3] model - scaling a variable with its value at the critical point
  • Friction force theory[3] - internal sliding surface analogy to a sliding box on an inclined surface
    • Multi- and one-parameter version of friction force theory
  • Transition state analogy - molecular energy needed to squeeze into a vacancy analogous to molecules locking into each other in a chemical reaction
    • Free volume theory[3] - molecular energy needed to jump into a vacant position in the neighboring surface
    • Significant structure theory[3] - based on Eyring's concept of liquid as a blend of solid-like and gas-like behavior / features

Selected contributions from these development directions is displayed in the following sections. This means that some known contributions of research and development directions are not included. For example, is the group contribution method applied to a shear viscosity model not displayed. Even though it is an important method, it is thought to be a method for parameterization of a selected viscosity model, rather than a viscosity model in itself.

The microscopic or molecular origin of fluids means that transport coefficients like viscosity can be calculated by time correlations which are valid for both gases and liquids, but it is computer intensive calculations. Another approach is the Boltzmann equation which describes the statistical behaviour of a thermodynamic system not in a state of equilibrium. It can be used to determine how physical quantities change, such as heat energy and momentum, when a fluid is in transport, but it is computer intensive simulations.

From Boltzmann's equation one may also analytical derive (analytical) mathematical models for properties characteristic to fluids such as viscosity, thermal conductivity, and electrical conductivity (by treating the charge carriers in a material as a gas). See also convection–diffusion equation. The mathematics is so complicated for polar and non-spherical molecules that it is very difficult to get practical models for viscosity. The purely theoretical approach will therefore be left out for the rest of this article, except for some visits related to dilute gas and significant structure theory.

Use, definition and dependenceEdit

The classic Navier-Stokes equation is the balance equation for momentum density for an isotropic, compressional and viscous fluid that is used in fluid mechanics in general and fluid dynamics in particular:


On the right hand side is (the divergence of) the total stress tensor   which consists of a pressure tensor   and a dissipative (or viscous or deviatoric) stress tensor  . The dissipative stress consists of a compression stress tensor   (term no. 2) and a shear stress tensor   (term no. 3). The rightmost term   is the gravitational force which is the body force contribution, and   is the mass density, and   is the fluid velocity.


For fluids, the spatial or Eularian form of the governing equations is preferred to the material or Lagrangian form, and the concept of velocity gradient is preferred to the equivalent concept of strain rate tensor. Stokes assumptions for a wide class of fluids therefore says that for an isotropic fluid the compression and shear stresses are proportional to their velocity gradients,   and   respectively, and named this class of fluids for Newtonian fluids. The classic defining equation for volume viscosity   and shear viscosity   are respectively:


The classic compression velocity "gradient" is a diagonal tensor that describes a compressing (alt. expanding) flow or attenuating sound waves:


The classic Cauchy shear velocity gradient, is a symmetric and traceless tensor that describes a pure shear flow (where pure means excluding normal outflow which in mathematical terms means a traceless matrix) around e.g. a wing, propellar, ship hull or in e.g. a river, pipe or vein with or without bends and boundary skin:


where the symmetric gradient matrix with non-zero trace is


How much the volume viscosity contributes to the flow characteristics in e.g. a choked flow such as convergent-divergent nozzle or valve flow is not well known, but the shear viscosity is by far the most utilized viscosity coefficient. The volume viscosity will now be abandoned, and the rest of the article will focus on the shear viscosity.

Another application of shear viscosity models is Darcy's law for multiphase flow.

   where a = water, oil, gas

and   and   are absolute and relative permeability, respectively. These 3 (vector) equations models flow of water, oil and natural gas in subsurface oil and gas reservoirs in porous rocks. Although the pressures changes are big, the fluid phases will flow slowly through the reservoir due to the flow restriction caused by the porous rock.

The above definition is based on a shear-driven fluid motion that in its most general form is modelled by a shear stress tensor and a velocity gradient tensor. The fluid dynamics of a shear flow is, however, very well illustrated by the simple Couette flow. In this experimental layout, the shear stress   and the shear velocity gradient   (where now  ) takes the simple form:


Inserting these simplifications gives us a defining equation that can be used to interpret experimental measurements:


where   is the area of the moving plate and the stagnant plate,   is the spatial coordinate normal to the plates. In this experimental setup, value for the force   is first selected. Then a maximum velocity   is measured, and finally both values are entered in the equation to calculate viscosity. This gives one value for the viscosity of the selected fluid. If another value of the force is selected, another maximum velocity will be measured. This will result in another viscosity value if the fluid is a non-Newtonian fluid such as paint, but it will give the same viscosity value for a Newtonian fluid such as water, petroleum oil or gas. If another parameter like temperature,  , is changed, and the experiment is repeated with the same force, a new value for viscosity will be the calculated, for both non-Newtonian and Newtonian fluids. The great majority of material properties varies as a function of temperature, and this goes for viscosity also. The viscosity is also a function of pressure and, of course, the material itself. For a fluid mixture, this means that the shear viscosity will also vary according to the fluid composition. To map the viscosity as a function of all these variables require a large sequence of experiments that generates an even larger set of numbers called measured data, observed data or observations. Prior to, or at the same time as, the experiments is a material property model (or short material model) proposed to describe or explain the observations. This mathematical model is called the constitutive equation for shear viscosity. It is usually an explicit function that contains some empirical parameters that is adjusted in order to match the observations as good as the mathematical function is capable to do.

For a Newtonian fluid, the constitutive equation for shear viscosity is generally a function of temperature, pressure, fluid composition:


where   is the liquid phase composition with molfraction   for fluid component i, and   and   are the gas phase and total fluid compositions, respectively. For a non-Newtonian fluid (in the sense of a generalized Newtonian fluid), the constitutive equation for shear viscosity is also a function of the shear velocity gradient:


The existence of the velocity gradient in the functional relationship for non-Newtonian fluids says that viscosity is generally not an equation of state, so the term constitutional equation will in general be used for viscosity equations (or functions). The free variables in the two equations above, also indicates that specific constitutive equations for shear viscosity will be quite different from the simple defining equation for shear viscosity that is shown further up. The rest of this article will show that this is certainly true. Non-Newtonian fluids will therefore be abandoned, and the rest of this article will focus on Newtonian fluids.

Dilute gas limit and scaled variablesEdit

Elementary kinetic theoryEdit

In textbooks on elementary kinetic theory[1] one can find results for dilute gas modeling that have widespread use. Derivation of the kinetic model for shear viscosity usually starts by considering a Couette flow where two parallel plates are separated by a gas layer. This non-equilibrium flow is superimposed on a Maxwell–Boltzmann equilibrium distribution of molecular motions.

Let   be the collision cross section of one molecule colliding with another. The number density   is defined as the number of molecules per (extensive) volume  . The collision cross section per volume or collision cross section density is  , and it is related to the mean free path   by


Combining the kinetic equations for molecular motion with the defining equation of shear viscosity gives the well known equation for shear viscosity for dilute gases:




where   is the Boltzmann constant,   is the Avogadro constant,   is the gas constant,   is the molar mass and   is the molecular mass. The equation above presupposes that the gas density is low (i.e. the pressure is low), hence the subscript zero in the variable  . This implies that the kinetic translational energy dominates over rotational and vibrational molecule energies. The viscosity equation displayed above further presupposes that there is only one type of gas molecules, and that the gas molecules are perfect elastic hard core particles of spherical shape. This assumption of particles being like billiard balls with radius  , implies that the collision cross section of one molecule can be estimated by


But molecules are not hard particles. For a reasonably spherical molecule the interaction potential is more like the Lennard-Jones potential or even more like the Morse potential. Both have a negative part that attracts the other molecule from distances much longer than the hard core radius, and thus models the van der Waals forces. The positive part models the repulsive forces as the electron clouds of the two molecules overlap. The radius for zero interaction potential is therefore appropriate for estimating (or defining) the collision cross section in kinetic gas theory, and the r-parameter (conf.  ) is therefore called kinetic radius. The d-parameter (where  ) is called kinetic diameter.

The macroscopic collision cross section   is often associated with the critical molar volume  , and often without further proof or supporting arguments, by


where   is molecular shape parameter that is taken as an empirical tuning parameter, and the pure numerical part is included in order to make the final viscosity formula more suitably for practical use. Inserting this interpretation of  , and use of reduced temperature  , gives


which implies that the empirical parameter   is dimensionless, and that   and   have the same units. The parameter   is a scaling parameter that involves the gas constant   and the critical molar volume  , and it used to scale the viscosity. In this article the viscosity scaling parameter will frequently be denoted by   which involve one or more of the parameters  ,  ,   in addition to critical temperature   and molar mass  . Incomplete scaling parameters, such as the parameter   above where the gas constant   is absorbed into the empirical constant, will often be encountered in practice. In this case the viscosity equation becomes


where the empirical parameter   is not dimensionless, and a proposed viscosity model for dense fluid will not be dimensionless if   is the common scaling factor. Notice that


Inserting the critical temperature in the equation for dilute viscosity gives


The default values of the parameters   and   should be fairly universal values, although   depends on the unit system. However, the critical molar volume in the scaling parameters   and   is not easily accessible from experimental measurements, and that is a significant disadvantage. The general equation of state for a real gas is usually written as


where the critical compressibility factor  , which reflects the volumetric deviation of the real gases from the ideal gas, is also not easily accessible from laboratory experiments. However, critical pressure and critical temperature are more accessible from measurements. It should be added that critical viscosity is also not readily available from experiments.

Uyehara and Watson (1944)[4] proposed to absorb a universal average value of   (and the gas constant  ) into a default value of the tuning parameter   as a practical solution of the difficulties of getting experimental values for   and/or  . The visocity model for a dilute gas is then


By inserting the critical temperature in the formula above, the critical viscosity is calculated as


Based on an average critical compressibility factor of   and measured critical viscosity values of 60 different molecule types, Uyehara and Watson (1944)[4] determined an average value of   to be


The cubic equation of state (EOS) are very popular equations that are sufficiently accurate for most industrial computations both in vapor-liquid equilibrium and molar volume. Their weakest points are perhaps molar volum in the liquid region and in the critical region. Accepting the cubic EOS, the molar hard core volume   can be calculated from the turning point constraint at the critical point. This gives


where the constant   is a universal constant that is specific for the selected variant of the cubic EOS. This says that using  , and disregarding fluid component variations of  , is in practice equivalent to say that the macroscopic collision cross section is proportional to the hard core molar volume rather than the critical molar volume.

In a fluid mixture like a petroleum gas or oil there are lots of molecule types, and within this mixture there are families of molecule types (i.e. groups of fluid components). The simplest group is the n-alkanes which are long chains of CH2-elements. The more CH2-elements, or carbon atoms, the longer molecule. Critical viscosity and critical thermodynamic properties of n-alkanes therefore show a trend, or functional behaviour, when plotted against molecular mass or number of carbon atoms in the molecule (i.e. carbon number). Parameters in equations for properties like viscosity usually also show such trend behaviour. This means that


This says that the scaling parameter   alone is not a true or complete scaling factor unless all fluid components have a fairly similar (and preferably spherical) shape.

The most important result of this kinetic derivation is perhaps not the viscosity formula, but the semi-empirical parameter   that is used extensively throughout the industry and applied science communities as a scaling factor for (shear) viscosity. The literature often reports the reciprocal parameter and denotes it as  .

The dilute gas viscosity contribution to the total viscosity of a fluid will only be important when predicting the viscosity of vapors at low pressures or the viscosity of dense fluids at high temperatures. The viscosity model for dilute gas, that is shown above, is widely used throughout the industry and applied science communities. Therefore, many researchers do not specify a dilute gas viscosity model when they propose a total viscosity model, but leave it to the user to select and include the dilute gas contribution. Some researchers do not include a separate dilute gas model term, but propose an overall gas viscosity model that cover the entire pressure and temperature range they investigated.

In this section our central macroscopic variables and parameters and their units are temperature   [K], pressure   [bar], molar mass   [g/mol], low density (low pressure or dilute) gas viscosity   [μP]. It is, however, common in the industry to use another unit for liquid and high density gas viscosity   [cP].

Kinetic theoryEdit

From Boltzmann's equation Chapman and Enskog derived a viscosity model for a dilute gas.


where   is (the absolute value of) the energy-depth of the potential well (see e.g. Lennard-Jones interaction potential). The term   is called the collision integral, and it is occurs as a general function of temperature that the user must specify, and that is not a simple task. This illustrates the situation for the molecular or statistical approach: The (analytical) mathematics gets incredible complex for polar and non-spherical molecules making it very difficult to achieve practical models for viscosity based on a statistical approach. The purely statistical approach will therefore be left out in the rest of this article.

Empirical correlationEdit

Zéberg-Mikkelsen (2001)[3] proposed empirical models for gas viscosity of fairly spherical molecules that is displayed in the section on Friction Force theory and its models for dilute gases and simple light gases. These simple empirical correlations illustrate that empirical methods competes with the statistical approach with respect to gas viscosity models for simple fluids (simple molecules).

Kinetic theory with empirical extensionEdit

The gas viscosity model of Chung et alios (1988)[5] is combination of the Chapman–Enskog(1964) kinetic theory of viscosity for dilute gases and the empirical expression of Neufeld et alios (1972)[6] for the reduced collision integral, but expanded empirical to handle polyatomic, polar and hydrogen bonding fluids over a wide temperature range. This viscosity model illustrates a successful combination of kinetic theory and empiricism, and it is displayed in the section of Significant structure theory and its model for the gas-like contribution to the total fluid viscosity.

Trend functions and scalingEdit

In the section with models based on elementary kinetic theory, several variants of scaling the viscosity equation was discussed, and they are displayed below for fluid component i, as a service to the reader.


Zéberg-Mikkelsen (2001)[3] proposed an empirical correlation for the   parameter for n-alkanes, which is


The critical molar volume of component i   is related to the critical mole density   and critical mole concentration   by the equation  . From the above equation for   it follows that


where   is the compressibility factor for component i, which is often used as an alternative to  . By establishing a trend function for the parameter   for a homologous series, groups or families of molecules, parameter values for unknown fluid components in the homologous group can be found by interpolation and extrapolation, and parameter values can easily re-generateat at later need. Use of trend functions for parameters of homologous groups of molecules have greatly enhanced the usefulness of viscosity equations (and thermodynamic EOSs) for fluid mixtures such as petroleum gas and oil.[2]

Uyehara and Watson (1944)[4] proposed a correlation for critical viscosity (for fluid component i) for n-alkanes using their average parameter   and the classical pressure dominated scaling parameter   :


Zéberg-Mikkelsen (2001)[3] proposed an empirical correlation for critical viscosity ηci parameter for n-alkanes, which is


The unit equations for the two constitutive equations above by Zéberg-Mikkelsen (2001) are


Inserting the critical temperature in the three viscosity equations from elementary kinetic theory gives three parameter equations.


The three viscosity equations now coalesce to a single viscosity equation


because a nondimensional scaling is used for the entire viscosity equation. The standard nondimensionality reasoning goes like this: Creating nondimensional variables (with subscript D) by scaling gives


Claiming nondimensionality gives


The collision cross section and the critical molar volume which are both difficult to access experimentally, are avoided or circumvented. On the other hand, the critical viscosity has appeared as a new parameter, and critical viscosity is just as difficult to access experimentally as the other two parameters. Fortunately, the best viscosity equations have become so accurate that they justify calculation in the critical point, especially if the equation is matched to surrounding experimental data points.

Classic mixing rulesEdit

Classic mixing rules for gasEdit

Wilke (1950)[7] derived a mixing rule based on kinetic gas theory


The Wilke mixing rule is capable of describing the correct viscosity behavior of gas mixtures showing a nonlinear and non-monotonical behavior, or showing a characteristic bump shape, when the viscosity is plotted versus mass density at critical temperature, for mixtures containing molecules of very different sizes. Due to its complexity, it has not gained widespread use. Instead, the slightly simpler mixing rule proposed by Herning and Zipperer (1936),[8] is found to be suitable for gases of hydrocarbon mixtures.

Classic mixing rules for liquidEdit

The classic Grunberg-Nissan (1949)[9] mixing rule for liquid mixture is


where   is the viscosity of the liquid mixture,   is the viscosity (equation) for fluid component i when flowing as a pure fluid, and   is the molfraction of component i in the liquid mixture. The Grunberg-Nissan mixing rule is equivalent to a mixing rule derived by Arrhenius (1887).[10]

A natural modification of the Grunberg-Nissan Mixing rule is


where   are empiric binary interaction coefficients that are special for the Grunberg-Nissan theory. Binary interaction coefficients are widely used in cubic EOS where they often are used as tuning parameters, especially if component j is an uncertain component (i.e. have uncertain parameter values).

Katti-Chaudhri (1964)[11] mixing rule is


where   is the partial molar volume of component i, and   is the molar volume of the liquid phase and comes from the vapor-liquid equilibrium (VLE) calculation or the EOS for single phase liquid.

A modification of the Katti-Chaudhri mixing rule is


where   is the excess activation energy of the viscous flow, and   is the energy that is characteristic of intermolecular interactions between component i and component j, and therefore is responsible for the excess energy of activation for viscous flow. This mixing rule is theoretically justified by Eyring's representation of the viscosity of a pure fluid according to Glasstone et alios (1941).[12] The quantity   has been obtained from the time-correlation expression for shear viscosity by Zwanzig (1965).[13]

Power seriesEdit

Very often one simply selects a known correlation for the dilute gas viscosity  , and subtracts this contribution from the total viscosity which is measured in the laboratory. This gives a residual viscosity term, often denoted  , which represents the contribution of the dense fluid,  .


The dense fluid viscosity is thus defined as the viscosity in excess of the dilute gas viscosity. This technique is often used in developing mathematical models for both purely empirical correlations and models with a theoretical support. The dilute gas viscosity contribution becomes important when the zero density limit (i.e. zero pressure limit) is approached. It is also very common to scale the dense fluid viscosity by the critical viscosity, or by an estimate of the critical viscosity, which is a characteristic point far into the dense fluid region. The simplest model of the dense fluid viscosity is a (truncated) power series of reduced mole density or pressure. Jossi et al. (1962)[14] presented such a model based on reduced mole density, but its most widespread form is the version proposed by Lohrenz et al. (1964)[15] which is displayed below.


The LBC-function is then expanded in a (truncated) power series with empirical coefficients as displayed below.


The final viscosity equation is thus


Local nomenclature list:

  •   : mole density [mol/cm3]
  •  : reduced mole density [1]
  •   : molar mass [g/mol]
  •   : critical pressure [atm]
  •   : temperature [K]
  •   : critical temperature [K]
  •   : critical molar volume [cm3/mol]
  •   : viscosity [cP]



The formula for   that was chosen by LBC, is displayed in the section called Dilute gas contribution.

Mixing rulesEdit


The subscript C7+ refers to the collection of hydrocarbon molecules in a reservoir fluid with oil and/or gas that have 7 or more carbon atoms in the molecule. The critical volume of C7+ fraction has unit ft3/lb mole, and it is calculated by


where   is the specific gravity of the C7+ fraction.


The molar mass   (or molecular mass) is normally not included in the EOS formula, but it usually enters the characterization of the EOS parameters.


From the equation of state the molar volume of the reservoir fluid (mixture) is calculated.


The molar volume   is converted to mole density   (also called mole concentration and denoted  ), and then scaled to be reduced mole density  .


Dilute gas contributionEdit

The correlation for dilute gas viscosity of a mixture is taken from Herning and Zipperer (1936)[8] and is


The correlation for dilute gas viscosity of the individual components is taken from Stiel and Thodos (1961)[16] and is




Corresponding state principleEdit

The principle of corresponding states (CS principle or CSP) was first formulated by van der Waals, and it says that two fluids (subscript a and z) of a group (e.g. fluids of non-polar molecules) have approximately the same reduced molar volume (or reduced compressibility factor) when compared at the same reduced temperature and reduced pressure. In mathematical terms this is


When the common CS principle above is applied to viscosity, it reads


Note that the CS principle was originally formulated for equilibrium states, but it is now applied on a transport property - viscosity, and this tells us that another CS formula may be needed for viscosity.

In order to increase the calculation speed for viscosity calculations based on CS theory, which is important in e.g. compositional reservoir simulations, while keeping the accuracy of the CS method, Pedersen et al. (1984, 1987, 1989)[17][18][2] proposed a CS method that uses a simple (or conventional) CS formula when calculating the reduced mass density that is used in the rotational coupling constants (displayed in the sections below), and a more complex CS formula, involving the rotational coupling constants, elsewhere.


The simple corresponding state principle is extended by including a rotational coupling coefficient   as suggested by Tham and Gubbins (1970).[19] The reference fluid is methane, and it is given the subscript z.


Mixing rulesEdit

The interaction terms for critical temperature and critical volume are


The parameter   is usually uncertain or not available. One therefore wants to avoid this parameter. Replacing   with the generic average parameter   for all components, gives


The above expression for   is now inserted into the equation for  . This gives the following mixing rule


Mixing rule for the critical pressure of the mixture is established in a similar way.


The mixing rule for molecular weight is much simpler, but it is not entirely intuitive. It is an empirical combination of the more intuitive formulas with mass weighting   and mole weighting  .


The rotational coupling parameter for the mixture is


Reference fluidEdit

The accuracy of the final viscosity of the CS method needs a very accurate density prediction of the reference fluid. The molar volume of the reference fluid methane is therefore calculated by a special EOS, and the Bendict-Webb-Rubin (1940)[20] equation of state variant suggested by McCarty (1974),[21] and abbreviated BWRM, is recommended by Pedersen et al. (1987) for this purpose. This means that the fluid mass density in a grid cell of the reservoir model may be calculated via e.g. a cubic EOS or by an input table with unknown establishment. In order to avoid iterative calculations, the reference (mass) density used in the rotational coupling parameters is therefore calculated using a simpler corresponding state principle which says that


The molar volume is used to calculate the mass concentration, which is called (mass) density, and then scaled to be reduced density which is equal to reciprocal of reduced molar volume because there is only on component (molecule type). In mathematical terms this is


The formula for the rotational coupling parameter of the mixture is shown further up, and the rotational coupling parameter for the reference fluid (methane) is


The methane mass density used in viscosity formulas is based on the extended corresponding state, shown at the beginning of this chapter on CS-methods. Using the BWRM EOS, the molar volume of the reference fluid is calculated as


Once again, the molar volume is used to calculate the mass concentration, or mass density, but the reference fluid is a single component fluid, and the reduced density is independent of the relative molar mass. In mathematical terms this is


The effect of a changing composition of e.g. the liquid phase is related to the scaling factors for viscosity, temperature and pressure, and that is the corresponding state principle.

The reference viscosity correlation of Pedersen et al. (1987)[18] is


The formulas for  ,  ,   are taken from Hanley et al. (1975).[22]

The dilute gas contribution is


The temperature dependent factor of the first density contribution is


The dense fluid term is


where exponential function is written both as   and as  . The molar volume of the reference fluid methane, which is used to calculate the mass density in the viscosity formulas above, is calculated at a reduced temperature that is proportional to the reduced temperature of the mixture. Due to the high critical temperatures of heavier hydrocarbon molecules, the reduced temperature of heavier reservoir oils (i.e. mixtures) can give a transferred reduced methane temperature that is in the neighborhood of the freezing temperature of methane. This is illustrated using two fairly heavy hydrocarbon molecules, in the table below. The selected temperatures are a typical oil or gas reservoir temperature, the reference temperature of the International Standard Metric Conditions for Natural Gas (and similar fluids) and the freezing temperature of methane ( ).

Pedersen et al. (1987) added a fourth term, that is correcting the reference viscosity formula at low reduced temperatures. The temperature functions   and   are weight factors. Their correction term is


Equation of state analogyEdit

Phillips (1912)[23] plotted temperature   versus viscosity   for different isobars for propane, and observed a similarity between these isobaric curves and the classic isothermal curves of the   surface. Later, Little and Kennedy (1968)[24] developed the first viscosity model based on analogy between   and   using van der Waals EOS. Van der Waals EOS was the first cubic EOS, but the cubic EOS has over the years been improved and now make up a widely used class of EOS. Therefore, Guo et al. (1997)[25] developed two new analogy models for viscosity based on PR EOS (Peng and Robinson 1976) and PRPT EOS (Patel and Teja 1982)[26] respectively. The following year T.-M. Guo (1998)[27][3] modified the PR based viscosity model slightly, and it is this version that will be presented below as a representative of EOS analogy models for viscosity.

PR EOS is displayed on the next line.


The viscosity equation of Guo (1998) is displayed on the next line.


To prepare for the mixing rules, the viscosity equation is re-written for a single fluid component i.


Details of how the composite elements of the equation are related to basic parameters and variables, is displayed below.




Mixing rulesEdit


Friction force theoryEdit

Multi-parameter friction force theoryEdit

The multi-parameter version of the friction force theory (short FF theory and FF model), also called friction theory (short F-theory), was developed by Quiñones-Cisneros et al. (2000, 2001a, 2001b and Z 2001, 2004, 2006),[28][29][30][3][31][32] and its basic elements, using some well known cubic EOSs, are displayed below.

It is a common modeling technique to accept a viscosity model for dilute gas ( ), and then establish a model for the dense fluid viscosity  . The FF theory states that for a fluid under shear motion, the shear stress   (i.e. the dragging force) acting between two moving layers can be separated into a term   caused by dilute gas collisions, and a term   caused by friction in the dense fluid.


The dilute gas viscosity (i.e. the limiting viscosity behavior as the pressure, normal stress, goes to zero) and the dense fluid viscosity (the residual viscosity) can be calculated by


where du/dy   is the local velocity gradient orthogonal to the direction of flow. Thus


The basic idea of QZS (2000) is that internal surfaces in a Couette flow acts like (or is analogue to) mechanical slabs with friction forces acting on each surface as they slide past each other. According to the Amontons-Coulomb friction law in classical mechanics, the ratio between the kinetic friction force   and the normal force   is given by


where   is known as the kinetic friction coefficient, A is the area of the internal flow surface,   is the shear stress and   is the normal stress (or pressure  ) between neighboring layers in the Couette flow.


The FF theory of QZS says that when a fluid is brought to have shear motion, the attractive and repulsive intermolecular forces will contribute to amplify or diminish the mechanical properties of the fluid. The friction shear stress term   of the dense fluid can therefore be considered to consist of an attractive friction shear contribution   and a repulsive friction shear contribution  . Inserting this gives us


The well known cubic equation of states (SRK, PR and PRSV EOS), can be written in a general form as


The parameter pair (u,w)=(1,0) gives the SRK EOS, and (u,w)=(2,-1) gives both the PR EOS and the PRSV EOS because they differ only in the temperature and composition dependent parameter / function a. Input variables are, in our case, pressure (P), temperature (T) and for mixtures also fluid composition which can be single phase (or total) composition  , vapor (gas) composition   or liquid (in our example oil) composition  . Output is the molar volume of the phase (V). Since the cubic EOS is not perfect, the molar volume is more uncertain than the pressure and temperature values.

The EOS consists of two parts that are related to van der Waals forces, or interactions, that originates in the static electric fields of the colliding parts /spots of the two (or more) colliding molecules. The repulsive part of the EOS is usually modeled as a hard core behavior of molecules, hence the symbol (Ph), and the attractive part (Pa) is based on the attractive interaction between molecules (conf. van der Waals force). The EOS can therefore be written as


Assume that the molar volume (V) is known from EOS calculations, and prior vapor-liquid equilibrium (VLE) calculations for mixtures. Then the two functions   and   can be utilized, and these functions are expected to be a more accurate and robust than the molar volume (V) itself. These functions are


The friction theory therefore assumes that the residual attractive stress   and the residual repulsive stress   are functions of the attractive pressure term   and the repulsive pressure term  , respectively.


The first attempt is, of course, to try a linear function in the pressure terms / functions.


All   coefficients are in general functions of temperature and composition, and they are called friction functions. In order to achieve high accuracy over a wide pressure and temperature ranges, it turned out that a second order term was needed even for non-polar molecules types such as hydrocarbon fluids in oil and gas reservoirs, in order to achieve a high accuracy at very high pressures. A test with a presumably difficult 3-component mixture of non-polar molecule types needed a third order power to achieve high accuracy at the most extreme super-critical pressures.


This article will concentrate on the second order version, but the third order term will be included whenever possible in order to show the total set of formulas. As an introduction to mixture notation, the above equation is repeated for component i in a mixture.


The unit equations for the central variables in the multi-parameter FF-model is


Friction functionsEdit

Friction functions for fluid component i in the 5 parameter model for pure n-alkane molecules are presented below.


Friction functions for fluid component i in the 7- and 8-parameter models are presented below.


The empirical constants in the friction functions are called friction constants. Friction constants for some n-alkanes in the 5 parameter model using SRK and PRSV EOS (and thus PR EOS) is presented in tables below. Friction constants for some n-alkanes in the 7 parameter model using PRSV EOS are also presented in a table below. The constant   for three fluid components are presented below in the last table of this table-series.



In the single phase regions, the mole volume of the fluid mixture is determined by the input variables are pressure (P), temperature (T) and (total) fluid composition  . In the two-phase gas-liquid region a vapor-liquid equilibrium (VLE) calculation splits the fluid into a vapor (gas) phase with composition   and phase mixture molfraction ng and a liquid phase (in our example oil) with composition   and phase mixture molfraction no. For liquid phase, vapor phase and single phase fluid the relation to VLE and EOS variables are


In a compositional reservoir simulator the pressure is calculated dynamically for each grid cell and each timestep. This gives dynamic pressures for vapor and liquid (oil) or single phase fluid. Assuming zero capillary pressure between hydrocarbon liquid (oil) and gas, the simulator software code will give a single dynamic pressure   which applies to both the vapor mixture and the liquid (oil) mixture. In this case the reservoir simulator software code may use




The friction model for viscosity of a mixture is


The cubic power term is only needed when molecules with a fairly rigid 2-D structure are included in the mixture, or the user requires a very high accuracy at exemely high pressures. The standard model includes only linear and quadratic terms in the pressure functions.

Mixing rulesEdit


where the empirical weight fraction is


The recommended values for   are

  •   gave best performance for SRK EOS
  •   gave best performance for PRSV EOS

These values are established from binary mixtures of n-alkanes using a 5-parameter viscosity model, and they seems to be used for 7- and 8-parameter models also. The motivation for this weight parameter  , and thus the  -parameter, is that in asymmetric mixtures like CH4 - C10H12, the lightest component tends to decrease the viscosity of the mixture more than linearly when plotted versus molfraction of the light component (or the heavy component).

The friction coefficients of some selected fluid components is presented in the tables below for the 5,7 and 8-parameter models. For convenience are critical viscosities also included in the tables.


One-parameter friction force theoryEdit

The one-parameter version of the friction force theory (FF1 theory and FF1 model) was developed by Quiñones-Cisneros et al. (2000, 2001a, 2001b and Z 2001, 2004),[28][29][30][3][31] and its basic elements, using some well known cubic EOSs, are displayed below.

The first step is to define the reduced dense fluid (or frictional) viscosity for a pure (i.e. single component) fluid by dividing by the critical viscosity. The same goes for the dilute gas viscosity.


The second step is to replace the attractive and repulsive pressure functions by reduced pressure functions. This will of course, affect the friction functions also. New friction functions are therefore introduced. They are called reduced friction functions, and they are of a more universal nature. The reduced frictional viscosity is


Returning to the unreduced frictional viscosity and rephrasinge the formula, gives


Critical viscosity is seldom measured and attempts to predict it by formulas are few. For a pure fluid, or component i in a fluid mixture, a formula from kinetic theory is often used to estimate critical viscosity.


where   is a constant, and critical molar volume Vci is assumed to be proportional to the collision cross section. The critical molar volume Vci is significantly more uncertain than the parameters Pci and Tci. To get rid of Vci, the critical compressibility factor Zci is often replaced by a universal average value. This gives


where   is a constant. Based on an average critical compressibility factor of Zc = 0.275 and measured critical viscosity values of 60 different molecule types, Uyehara and Watson (1944)[4] determined an average value of Kp to be


Zéberg-Mikkelsen (2001) proposed an empirical correlation for Vci, with parameters for n-alkanes, which is


where  . From the above equation and the definition of the compressibility factor it follows that


Zéberg-Mikkelsen (2001) also proposed an empirical correlation for ηci, with parameters for n-alkanes, which is


The unit equations for the two constitutive equations above by Zéberg-Mikkelsen (2001) are


The next step is to split the formulas into formulas for well defined components (designated by subscript d) with respect critical viscosity and formulas for uncertain components (designated by subscript u) where critical viscosity is estimated using   and the universal constant   which will be treated as a tuning parameter for the current mixture. The dense fluid viscosity (for fluid component i in a mixture) is then written as


The formulas from friction theory is then related to well defined and uncertain fluid components. The result is


However, in order to obtain the characteristic critical viscosity of the heavy pseudocomponents, the following modification of the Uyehara and Watson (1944) expression for the critical viscosity can be used. The frictional (or residual) viscosity is then written as


The unit equations are   and   and  .

Reduced friction functionsEdit


The unit equation of   is  .

The 1-parameter model have been developed based on single component fluids in the series from methane to n-octadecane (C1H4 to C18H38). The empirical parameters in the reduced friction functions above are treated as universal constants, and they are listed in the following table. For convenience are critical viscosities included in the tables for models with 5- and 7-parameters that was presented further up.



The mixture viscosity is given by


The mixture viscosity of well defined components is given by


The mixture viscosity function of uncertain components is given by


The mixture viscosity can be tuned to measured viscosity data by optimizing (regressing) the parameter  .

where the mixture friction coefficients are obtained by eq(I.7.45) through eq(I.7.47) and   and   are the attractive and repulsive pressure term of the mixture.

Mixing rulesEdit

The mixing rules for the well defined components are


QZS recommends to drop the dilute gas term for the uncertain fluid components which are usually the heavier (hydrocarbon) components. The formula is kept here for consistency. The mixing rules for the uncertain components are


Dilute gas limitEdit

Zéberg-Mikkelsen (2001)[3] proposed an empirical model for dilute gas viscosity of fairly spherical molecules as follows




The unit equations for viscosity and temperature are


The second term is a correction term for high temperatures. Note that most   parameters are negative.


Light gasesEdit

Zéberg-Mikkelsen (2001) proposed a FF-model for light gas viscosity as follows


The friction functions for light gases are simple