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Thermodynamic models for wax precipitation
Understanding the mechanisms and potential for wax precipitation are key factors in preventing production problems as a result of wax. Wax precipitation has a strong dependence on temperature and weak dependence on pressure. This page presents a general form of the thermodynamic relation used to define the K values for solid and liquid phases in equilibrium, and the effect of different simplifying assumptions and thermodynamic descriptions of the phases involved on the model results are examined.
Thermodynamics of solid/liquid equilibrium
The thermodynamic basis of solid/liquid equilibrium of components in a melt or dissolved in a solution is well established and is described in many standard texts (e.g., Prausnitz et al.[1]). The basic principles continue to be applied to more complex systems as researchers attempt to develop more accurate models of solid wax precipitation. Lira-Galeana and Hammami[2] reviewed experimental techniques and thermodynamic models for studying wax precipitation in petroleum fluids.
The predictive capability of the thermodynamic models is affected both by the form and assumptions of the models themselves and the characterization procedures used to quantify the number and properties of wax forming components present in a fluid.
Thermodynamic equilibrium
Thermodynamic models for predicting wax precipitation may be derived assuming single-component or multicomponent, single-phase or multiphase solid deposits. Regardless of which set of assumptions is chosen, the condition of thermodynamic equilibrium between phases is expressed as the equality of chemical potential for each component in all phases. For one solid phase in equilibrium with an oil, this condition is given by
where:
- μio and μis are the chemical potentials of component i in the oil and solid phases, respectively
- nc is the number of components. With the fundamental relation between chemical potential and fugacity of component i (nc)
the equilibrium relation also may be expressed in terms of fugacities:
where fio and fis are the fugacities of component i in the oil and solid phases, respectively.
Calculation of pure solid component fugacity
Calculation equations-of-state (EOSs) are not available to describe the volumetric behavior of the solid phase as a general function of temperature and pressure; therefore, thermodynamic solid-precipitation models are derived by relating the chemical potential of a pure solid to the chemical potential of the pure liquid at the same pressure and temperature in terms of experimentally known melting properties. Derivation of this expression is discussed in standard thermodynamics texts such as Prausnitz et al.[1] The most general form of this relationship, including multiple solid-phase transitions, is[3][4]
where:
- μpi,k = chemical potential of pure component
- ΔHif = enthalpy of fusion of component i,
- Tif = temperature of fusion (melting temperature) of component i
- ntr = number of solid state transitions,
- ΔHij,tr = enthalpy of the jth solid state transition of component i
- Tij,tr = jth solid state transition temperature of component i
- ΔCpi = (CPo,i - CPs,i), heat capacity of fusion of component i
- Pif = pressure of fusion (corresponding to Tif) of component i
- ΔCpij,tr = heat capacity of jth solid state transition of component i
- Δvi = (vo,i-vs,i), change of molar volume caused by fusion of component i
In the majority of wax precipitation models, multiple solid-state transitions are not considered, or the effects are lumped into the enthalpy of fusion and heat capacity of fusion terms. Removing these terms and applying the relation between chemical potential and fugacity given in Eq. 2, Eq. 4 can be written in terms of fugacities as
where is the fugacity of pure component i in phase state k (k = o, s).
K-value equations
Eq. 5 may be used directly to determine pure-solid-component fugacities, or it may be combined with activity- or fugacity-coefficient models to derive expressions for solid/liquid K values. This section gives the fundamental forms of these K-value equations. These equations then are used with various assumptions to perform solid/liquid or solid/liquid/vapor equilibrium calculations.
Activity-coefficient models
Activity coefficients can be defined in terms of fugacities as[5]
where γi = activity coefficient of component i in a mixture, fi = fugacity of component i in the mixture, xi = mole fraction of component i in the mixture, and = standard state fugacity of component i. The standard state fugacity is the fugacity of component i in the same state and at the same temperature as the mixture and at an arbitrarily chosen pressure and composition. If the activity coefficients are defined with reference to an ideal solution in the sense of Raoult’s law, then the pressure is chosen as the system pressure and the composition is chosen as pure component i. The development of the equations presented here uses this definition.
An expression for solid/liquid K values in terms of activity coefficients can be derived with the use of the definition of Eq. 6 as
where:
- Kis = solid/liquid K value for component i
- xik = mole fraction of component i in phase k (k = o, s)
- γik = activity coefficient of component i in phase k (k = o, s)
- = fugacity of pure component i in phase k (k = o, s)
For use with activity-coefficient models, the condition of equilibrium between the solid and liquid phases given in Eq. 3 can be substituted into Eq. 5 to yield the following relation in terms of pure component fugacities.
Substituting Eq. 8 into Eq. 7 then gives the general relationship for solid/liquid K values in terms of activity coefficients and melting properties:
Fugacity-coefficient models
For use with EOSs, it is convenient to write the solid/liquid K-value equation in terms of the wax melting properties and fugacity coefficients, as opposed to activity coefficients. Fugacity coefficients are defined as
where:
- = fugacity coefficient of pure component i in phase state k
- Φik = fugacity coefficient of component i in phase k
Substituting the fugacity-coefficient definitions, Eq. 5 can be rearranged to give the solid/liquid K-value expression
Mixed-activity and fugacity-coefficient models
The use of the fugacity coefficient as defined in Eq. 11 for the liquid phase and the activity coefficient as defined in Eq. 6 for the solid phase leads to the following equation for the solid/liquid K values when the equality of fugacity condition is applied.
This formula is convenient when the fluid-phase fugacities are determined with an EOS and the solid-phase activity coefficient is determined with another model.
Pure ideal solid model
In Eq. 9, the last term in the exponential accounting for the difference in molar volume between the solid and liquid as a function of pressure is usually the smallest and is most often neglected. The heat-capacity term is of larger magnitude but also is assumed negligible in many applications. If the nonidealities of the oil and solid phases also are considered to be small (i.e., γio/γis = 1) and the solid phase is assumed to be a pure component, the equation of ideal solubility results in
This equation may be regarded as being based on the Clausius-Clapeyron or van’t Hoff equations.[6]
Reddy[7] reported one application of the ideal solubility equation. Eq. 14 was used to determine the cloud points and amounts of precipitated wax for synthetic fuels and diesels. In this case, only n-paraffins were assumed to precipitate. For the synthetic fuels, measured quantities of n-paraffins were combined with a solvent. For the diesel fuels, the amounts of n-paraffins up to C27 were determined experimentally. The ideal solubility equation was used to convert the amounts of all n-paraffins in a system to an equivalent amount of reference paraffin. The solubility behavior of the reference component, n-eicosane, was determined experimentally. The mixtures then were treated as binary solute/solvent systems for computation. The predicted amount of wax precipitated at one temperature below the cloud point is compared with the experimental values in Fig. 1. These results illustrate the ability of the ideal solubility equation to correlate correctly experimentally observed trends, provided the distribution of wax-forming components is well defined.
Fig. 1 – Ideal solubility model predictions compared with measured values for composition of wax formed in a synthetic fuel blend. (Reprinted from Fuel, Vol. 65, S.R. Reddy, “A Thermodynamic Model for Predicting n-Paraffin Crystallization in Diesel Fuels,” pages 1647-1652, Copyright 1986, with permission from Elsevier Science).
The ideal solubility equation also was used by Weingarten and Euchner[8] for predicting wax precipitation from live reservoir fluids. Experimental determination of wax crystallization temperatures (cloud points) for two reservoir fluids was performed at 10 different bubblepoint pressures during differential-liberation experiments. Constants relating the enthalpy of fusion and temperature of fusion were determined by linear regression to the experimental data. Fig. 2 shows a comparison of the crystallization temperature predicted by the model to the experimental values. In this implementation, no characterization of the feed is necessary. The precipitated wax is treated as a single component. The model is able to only approximately reproduce an important trend in the data as a function of pressure: at high pressures, at which only small amounts of the lightest gases are being liberated, the crystallization temperature increases slowly with decreasing pressure; at lower pressures, at which more gas and heavier gas components are liberated, the crystallization temperature increases more rapidly with decreasing pressure.
Fig. 2 – Crystallization temperatures fitted to ideal solution theory.[8]
Solid-solution models
Wax models describing the precipitated solid as a single-phase multicomponent solution have been used in a large number of studies. The solid phase has most often been modeled as an ideal or regular solution. The fluid phases are modeled with the regular solution theory, Flory-Huggins theory, or EOSs.
Regular solid-solution models
Regular solution theory, as developed by Scatchard and Hildebrand, refers to mixtures with zero-excess entropy provided that there is no volume change of mixing. The Scatchard-Hildebrand equation for activity coefficients is[1]
where:
- δik = solubility parameter for pure component i in phase k
- = volume fraction average solubility parameter for phase k
The volume fraction average solubility parameter for a phase is given by:
At conditions far removed from the critical point, the solubility parameter for a component in the oil phase may be expressed in terms of the enthalpy of vaporization and the molar volume of the component.
Won[9] proposed a modified regular solution theory in which the solubility parameter for a component in the solid phase is given by
With Eq. 15 and assuming that vis = vio, the activity-coefficient ratio can be described by
Substituting Eq. 19 into Eq. 9 and assuming the pressure and heat-capacity terms are negligible gives the final equation used by Won[9] for the solid/liquid K values as
Won also presented correlations for the heat of fusion, temperature of fusion, and molar volume as functions of molecular weight and tabulates values of the solubility parameters for the liquid and solid phases. The correlations are applicable to normal paraffins. The heat of fusion is given by
where Mi is the molecular weight of component i. The heat of fusion from Eq. 21 is approximately equal to the sum of the heat of fusion and one-half the heat of transition for molecules heavier than C22 and approximately equal to the heat of fusion for odd carbon number molecules lighter than C22. The temperature of fusion is given by
and the molar volume is given by
In Won’s[9] model, solid/liquid/vapor equilibrium is determined. Liquid/vapor K values are calculated with the Soave-Redlich-Kwong EOS.[10] These K values are used with the solid/liquid K values in a three-phase flash algorithm to determine the solid/liquid/vapor-phase split as a function of temperature and pressure. There is an inconsistency in this technique in that the liquid properties are calculated from an activity-coefficient model for the solid/liquid K values and from an EOS for the vapor/liquid K values. Despite this inconsistency, Won’s technique has some important advantages over the ideal solubility models presented previously. These advantages include accounting for nonidealities in the solid and liquid phases and accounting for the simultaneous effects of pressure, temperature, and vaporization or solution of gas in the liquid on solid precipitation.
Won[9] applied this method to a hydrocarbon gas defined as a mixture of single carbon number (SCN) fractions from C1 to C40. These SCN fractions are assumed to have paraffinic properties as given by Eqs. 21 through 23. The feed composition is determined by extrapolating the measured mole fractions of C15 through C19. Fig. 3 shows the effect of temperature on the molar-phase splits for this feed gas. The cloud-point temperature can be seen as the highest temperature at which the solid phase exists, just below 310°K. The amount of solid increases rapidly as the temperature is decreased below this point. Fig. 4 shows the effect of pressure on the phase equilibrium.
Fig. 3 – Effect of temperature on the phase equilibria of a gas condensate predicted with the activity-coefficient model with regular-solution theory. (Reprinted from Fluid Phase Equilibria, Vol. 30, K.W. Won, “Thermodynamics for Solid-Liquid-Vapor Equilibria: Wax Phase Formation From Heavy Hydrocarbon Mixtures,” pages 265-279, Copyright 1986, with permission from Elsevier Science.)
Fig. 4 – Effect of pressure on the phase equilibria of a gas condensate predicted with the activity-coefficient model with regular-solution theory. (Reprinted from Fluid Phase Equilibria, Vol. 30, K.W. Won, “Thermodynamics for Solid-Liquid-Vapor Equilibria: Wax Phase Formation From Heavy Hydrocarbon Mixtures,” pages 265-279, Copyright 1986, with permission from Elsevier Science.)
Regular solution theory model for liquid phase
Pedersen et al.[11] use the general form of the solid/liquid K-value relation as given in Eq. 9, including the heat-capacity term but neglecting the pressure term. This results in the following equation for the K values:
The activity-coefficient ratio is calculated with the regular solution theory (Eq. 19), as in Won’s[9] model. Correlations are given for the solubility parameters of paraffins in the oil and solid phases as
where Ci is the carbon number of component i. Won’s correlation for the enthalpy of formation (Eq. 22) is modified as
and the model is completed by defining a relation for the heat-capacity difference as
Constants a1 through a5 were determined by a least-squares fit to the data of Pedersen et al.[12] as:
- a1 = 0.5914 (cal/cm3)0.5
- a2 = 5.763 (cal/cm3)0.5
- a3 = 0.5148
- a4 = 0.3033 cal/(g•K)
- a5 = 0.635×10-4 cal/(g•K2)
The oils were characterized on the basis of experimentally determined SCN fraction distributions. The fractions are subdivided into a paraffinic part and a naphthenic plus aromatic (NA) part. The NA fractions are given solubility parameters 20% higher than those obtained from Eqs. 25 and 26, while the enthalpy of formation for the NA fractions is set to 50% of the value calculated from Eq. 27.
Pedersen et al.[11] compared experimental wax precipitation as a function of temperature with model predictions for 16 crude oils. Only liquid/solid equilibrium was calculated. See graphics in Pederson et al.[11] for comparison of experimental results and full model predictions.
Internally consistent model with EOS for fluid phases
Mei et al.[13] applied the mixed activity/fugacity coefficient model given in Eq. 13 with a three-phase flash algorithm, in conjunction with liquid/vapor K values obtained from the Peng-Robinson EOS. As opposed to Won’s model,[9] this form maintains internal consistency with the use of the EOS for all fluid phase calculations and uses regular-solution theory only for the solid solution. The fugacity of the pure solid is calculated with Eq. 8, neglecting the pressure effect. Solid-solubility parameters required for regular-solution theory are calculated with a correlation given by Thomas et al.[14] Won’s correlations[9] for enthalpy of fusion, temperature of fusion, and molar volume are used with additional adjustable coefficients. A heat capacity of fusion correlation of the form given by Pedersen[15] completes the model.
Fluids used in the study were characterized on the basis of experimental SCN analysis to C40. No further subdivision of the components into P, N, and A subfractions was performed. A good match to experimental cloud points and wax precipitation amounts as a function of temperature was attained through the adjustment of five correlation coefficients.
Ideal solid-solution models
Applying the assumptions that the solid phase may be considered an ideal solution, the heat capacity terms are negligible, and the pressure terms are negligible, the K-value expression from Eq. 9 can be written as
Flory-Huggins model for the liquid phase
Flory and Huggins derived expressions for the thermodynamic properties of polymer solutions. A key parameter in determining the properties of these mixtures was found to be the large difference in molecular size between the polymer and the solvent species. The same situation is found in petroleum fluids, in which the large molecules of the heavy end are in solution with much smaller hydrocarbons. Flory-Huggins theory has been applied to asphaltene precipitation modeling as discussed in Thermodynamic models for asphaltene precipitation.
Hansen et al.[16] used the generalized polymer-solution theory given by Flory[17] to derive an expression for the activity coefficient of a component in the liquid phase. Eq. 29 then was applied to liquid/solid equilibrium calculations. Characterization of the oils is done on the basis of experimental determination of the SCN fraction distribution to at least C20+. Each of the SCN fractions then is divided into two subfractions: the aromatic part and the combined paraffinic and naphthenic part. Flory interaction parameters are calculated between the subfractions with a group-contribution method. Although good results were obtained, the resulting expression is complicated and the model has not been used by other researchers.
Ideal solution model for the liquid phase
Erickson et al.[18] used Eq. 29 with the additional assumption that the liquid phase is also an ideal solution. These authors note that the heat of fusion and melting-temperature terms are of much greater importance than the activity-coefficient terms for prediction of liquid/solid equilibria of stabilized liquids, justifying the use of the ideal solubility equation. Won’s correlation[9] for melting temperature as given in Eq. 22 is used for n-alkanes. A modification of this expression is used for all other species in the fluid. A single constant multiplying Won’s enthalpy of fusion correlation is used as an adjustable parameter to enable a better fit of the experimental data.
Erickson et al.[18] applied the model to stabilized oils with detailed experimental compositional analysis, which allows a direct determination of the amount of n-alkanes in each SCN fraction up to carbon numbers of 35 or 40. Extrapolation to C50 or higher is then performed. They also apply a "staged" equilibrium flash, which assumes that once a solid forms, it does not remix with additional solid that precipitates at lower temperatures. Fig. 5 compares model results with experimental data.
Fig. 5 – Comparison of multicomponent ideal solubility model predictions and experimental wax-precipitation amounts as a function of temperature.[18]
EOS models for liquid and vapor phases
Brown et al.[19] used a simplification of the fugacity coefficient form of the solid/liquid K-value expression (Eq. 12) to study the effects of pressure and light components on wax formation. The assumptions used are that the heat capacity difference is negligible, the solid phase can be considered an ideal solution, Δvi is constant, and pif is small compared with p. Applying these conditions leads to the final K-value expression:
The melting temperature and heat of fusion terms are calculated with the correlations given by Erickson et al.,[18] and the molar-volume difference is correlated as function of molecular weight. Brown et al. used the simplified perturbed-hard-chain theory EOS to calculate the fugacity coefficients. A correlation was developed for binary-interaction parameters of the paraffin components. The fluid-characterization method is the same as that described for the model of Erickson et al.[18]
Model predictions are compared with experimental data in Fig. 6 for a live fluid with a bubblepoint of 285 bar. The model predictions show that increasing the pressure from atmospheric (dead) oil causes a decrease in the cloud-point temperature as light ends dissolve in the oil phase. The light ends increase the solubility of heavy-wax components in the oil. A minimum in the cloud point is achieved at the bubblepoint of the oil. Further pressure increase in the single-phase region causes an increase in the cloud-point temperature.
Fig. 6 – Ideal solubility model with SPHCT EOS; effect of pressure on cloud-point temperatures for a live oil.[19]
Pedersen[15] used the fugacity-coefficient model of Eq. 30 with the additional simplification that the pressure effects were neglected, resulting in the following expression for the solid/liquid K values:
The Soave-Redlich-Kwong EOS is used to determine the fugacity coefficients for liquid and vapor phases. The characterization of the fluid is performed on the basis of a standard extended compositional analysis in which the mole fraction, molecular weight, and density of each SCN fraction is given. Pedersen[15] developed an empirical expression to calculate the mole fraction of the potentially wax-forming part of any SCN fraction. This approach is in contrast to the characterization procedure of Erickson et al.,[18] in which all the subfractions of a SCN fraction may potentially enter the wax phase, but the parameters of the nonnormal alkane fractions are defined such that they will enter the solid phase in lesser amounts.
Three adjustable parameters are used in the expression to determine the mole fraction of the wax-forming part of each SCN fraction. Fig. 7 shows example results for the model comparing the predicted and experimental amount of wax precipitated as a function of temperature.
Fig. 7 – EOS fluid/ideal solid model: comparison of predicted and experimental wax precipitation amounts as a function of temperature.[15]
Multiple-pure-solid-phase (multisolid) models
All the models discussed up to this point treat the deposited wax as a single phase, consisting of either a pure component or a mixture of components as a solid solution. As discussed in Asphaltenes and waxes, experimental work on binary-alkane mixtures shows that the components can separate into two immiscible solid phases, where each phase is essentially a pure component. Solid-phase transitions also are observed in crude oils.
Lira-Galeana et al.[20] developed a thermodynamic model for wax precipitation based on the concept that the precipitated wax is made up of several solid phases, at which each phase consists of a single component or pseudocomponent. From stability considerations, a component may exist as a pure solid if the following inequality is satisfied:
The number of solid-forming components and the number of solid phases, n s , is determined from Eq. 32. Once the number of solid phases is known, the phase-equilibrium relationships for vapor, liquid, and solid are given by
Eq. 8 is used, neglecting pressure effects, to obtain the pure-solid fugacity. The pure-liquid fugacity is obtained from the Peng-Robinson EOS,[21] as are the component fugacities in the liquid and vapor phases.
In the original multisolid-wax model presented by Lira-Galeana et al.,[20] the fluids are characterized by splitting the C7+ fraction into 7 to 12 pseudocomponents. No further subdivision of the pseudocomponents into P, N, or A fractions is performed. Instead, melting temperature and enthalpy of fusion correlations are developed to define properties that represent an average of the three subgroups. These correlations weight the aromatic properties more heavily for heavier molecular-weight pseudocomponents. The heat capacity of fusion is given by the correlation of Pedersen et al.,[12] as shown in Eq. 28. Fig. 8 shows experimental data and predicted results of the model.
Fig. 8 - Multisolid-wax model: comparison of predicted and experimental wax-precipitation amounts as a function of temperature. [After Lira-Galeana, C., Firoozabadi, A., and Prausnitz, J.M.: “Thermodynamics of Wax Precipitation in Petroleum Mixtures,” AlChE J. (1996) V. 42, 239. Reproduced with permission of the American Institute of Chemical Engineers. Copyright © 1996 AlChE. All rights reserved.]
Pan et al.[22] also have used the multisolid-wax model but with a different fluid-characterization procedure. The characterization is based on experimental SCN analysis. Every five consecutive carbon number fractions are lumped together. The relative amounts of the P, N, and A subfractions are determined experimentally or with correlations. Melting temperature and enthalpy of fusion properties are assigned to the paraffinic subfractions with Won’s correlations.[9] For naphthenes and aromatics, the correlations of Lira-Galeana et al.[20] were used, with the exception of the enthalpy of fusion for aromatics, which was fit with a new correlation independent of the molecular weight. For the heat capacity of fusion, the correlation of Pedersen et al.[12] was used for all components. Results of the model for a synthetic oil at 110 bar are shown in Fig. 9, illustrating the reduction in cloud point and also the reduction in amount of wax precipitated with the addition of methane to the system.
Fig. 9 – Multisolid-wax model with PNA characterization: effect of C1 on amount of precipitated wax.[22]
Multisolid-wax model including enthalpies of transition
Nichita et al.[4] used Eq. 4 to derive an expression for the ratio between the pure-solid and pure-liquid fugacities including the effect of multiple solid-state transitions. Assumptions used in the derivation are that the heat capacity of fusion is constant, the heat capacities of transition are negligible, the solid/liquid molar-volume difference is constant, and the terms for the enthalpies of transition are all evaluated at the temperature of the first transition. The authors state that this treatment of the enthalpies of transition may lead to relative differences in results of up to 10% compared with lumping the enthalpies of transition in with the enthalpy of fusion. Applying these considerations results in
Ungerer et al.[23] derived a similar expression with multiple enthalpies of transition; how-ever, the enthalpy terms are evaluated at the fusion temperature rather than the first transition temperature. The model is applied with a single pure-component-solid phase. Nichita et al.[4] used Eq. 35 with the modified multisolid-wax model presented in Pan et al.,[22] including the correlations for all component properties except enthalpies of fusion and enthalpies of transition; new correlations are presented for these properties. The model of Nichita et al.[4] is used with the Peng-Robinson EOS to calculate a pressure-temperature phase diagram, shown in Fig. 10, for a synthetic fluid with phenanthrene as the precipitating component. The binary-interaction parameter between methane and phenanthrene was adjusted to match the vapor/liquid dewpoint.
Fig. 10 – Multisolid-wax model with multiple-phase transitions: phase diagram for a synthetic gas mixture with phenanthrene.[4]
Excess Gibbs energy models
Activity coefficients are related to the partial molar excess Gibbs energy for a component i, , and the total excess Gibbs energy for a phase, GE, by
Excess free-energy models thus can be used with the solid/liquid K-value equation expressed in terms of activity coefficients for wax-precipitation modeling.
Coutinho and coworkers published a number of studies on modeling paraffin-wax formation from synthetic and real petroleum fluids.[24][25][26][27] In these works, an equation is used for the pure-component solid to liquid-fugacity ratio similar to that given in Eq. 35, with the additional assumption that only a single enthalpy of transition term is used and the pressure effect is neglected. This results in the following solid/liquid K- value expression in terms of activity coefficients:
The liquid-phase activity coefficient is given by
where the combinatorial free-volume contribution, , is obtained from a Flory free-volume model, and the residual contribution, lnγior , is obtained from the UNIFAC model, which is based on the universal quasichemical (UNIQUAC) equation. Coutinho et al.[25] contains more detail and references on these models.
Excess Gibbs energy models are used for the solid phase. A modified Wilson’s equation with one adjustable parameter was used initially.[26] Then, a predictive version of the UNIQUAC equation was developed,[24] which incorporates multiple-mixed-solid phases and is used to predict wax formation in jet and diesel fuels.[27] An analysis of the amounts of the individual n-alkanes is required for the fluid characterization. The N and A subfractions of a SCN fraction can be treated separately or lumped as a single pseudocomponent. The accuracy of the model is very good (see images in Coutinho et al. showing model results versus experimental data).
Pauly et al.[28] presented further development of the excess Gibbs energy model. In this model, the modified Wilson equation, as given by Coutinho and Stenby,[26] is used for the activity coefficients in the solid phase at atmospheric pressure. The Poynting factor is used to determine the high-pressure solid fugacity from the fugacity determined at atmospheric pressure. The liquid phase is modeled with an EOS/GE model. This combination of fluid and solid treatments yields good results for prediction of solid/liquid and solid/liquid/vapor phase boundaries up to 200 Mpa for binary and multicomponent systems of n-alkanes. The quality of the predictions is a result of the treatment of the pressure effect on the solid phase and the EOS/GE model, which guarantees continuity between fugacities of the fluid and solid phases.
Comparison of models
Pauly et al.[27] compared the models of Won,[9] Pedersen et al.,[11] Hansen et al.,[16] Coutinho and Stenby,[26] Ungerer et al.,[23] and the ideal solution model. The models are tested on systems composed of n-decane and a heavy fraction of normal alkanes from C18 to C30. Fig. 11 compares the total amount of solid precipitate as a function of temperature for the models with experimental data. The solid-solution models overpredict the cloud-point temperature and the amount of solid precipitated, while the multisolid model gives better results for the cloud point but underpredicts the amount of wax precipitated, at least for the higher temperature region. Coutinho and Stenby’s model[26] gives a very good match of the data.
Fig. 11 – Amount of solids precipitated as a function of temperature for a mixture of n-alkanes predicted with various models. (Reprinted from Fluid Phase Equilibria, Vol. 149, J. Pauly, C. Dauphin, and J.L. Daridon, “Liquid-Solid Equilibria in a Decane + Multi-Paraffins System,” pages 191-207, Copyright 1998, with permission from Elsevier Science.)
Nichita et al.[4] also compared their modification of the multisolid-wax model with a solid-solution model. The solid phase is assumed to be ideal, and the liquid phase is described by the EOS. Results for the two models are compared in Fig. 12 for three synthetic mixtures of n-decane with n-alkanes from C18 to C30. As in the comparison performed by Pauly et al.,[29] the solid-solution model overpredicts the cloud-point temperature and the amount of wax precipitated, while the multisolid-wax model gives good estimates of the cloud-point temperature yet underpredicts the amount of wax precipitated.
Fig. 12 – Comparison of multisolid- and solid-solution wax precipitation models.[4]
Nomenclature
References
- ↑ 1.0 1.1 1.2 Prausnitz, J.M., Lichtenthaler, R.N., and de Azevedo, E.G. 1999. Molecular Thermodynamics of Fluid-Phase Equilibria, third edition. Upper Saddle River, New Jersey: International Series in the Physical and Chemical Engineering Sciences, Prentice Hall PTR.
- ↑ Lira-Galeana, C. and Hammami, A. 2000. Wax Precipitation from Petroleum Fluids: A Review. In Asphaltenes and Asphalts, ed. T.F. Yen and G.V. Chilingarian, Vol. 2, No. 40B, Chap. 21, 557–608. Amsterdam, The Netherlands: Developments in Petroleum Science, Elsevier Science B.V.
- ↑ Choi, P.B. and McLaughlin, E. 1983. Effect of a phase transition on the solubility of a solid. AIChE J. 29 (1): 150-153. http://dx.doi.org/10.1002/aic.690290121
- ↑ 4.0 4.1 4.2 4.3 4.4 4.5 4.6 Nichita, D.V., Goual, L., and Firoozabadi, A. 1999. Wax Precipitation in Gas Condensate Mixtures. Presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, USA, 3-6 October. SPE-56488-MS. http://dx.doi.org/10.2118/56488-MS
- ↑ Firoozabadi, A. 1999. Thermodynamics of Hydrocarbon Reservoirs. New York: McGraw-Hill.
- ↑ Walas, S.M. 1985. Phase Equilibria in Chemical Engineering. Boston, Massachusetts: Butterworth Publishers.
- ↑ Reddy, S.R. 1986. A thermodynamic model for predicting n-paraffin crystallization in diesel fuels. Fuel 65 (12): 1647-1652. http://dx.doi.org/10.1016/0016-2361(86)90263-2
- ↑ 8.0 8.1 Weingarten, J.S. and Euchner, J.A. 1988. Methods for Predicting Wax Precipitation and Deposition. SPE Prod Eng 3 (1): 121-126. SPE-15654-PA. http://dx.doi.org/10.2118/15654-PA
- ↑ 9.0 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9 Won, K.W. 1986. Thermodynamics for solid solution-liquid-vapor equilibria: wax phase formation from heavy hydrocarbon mixtures. Fluid Phase Equilib. 30 (0): 265-279. http://dx.doi.org/10.1016/0378-3812(86)80061-9
- ↑ Soave, G. 1972. Equilibrium constants from a modified Redlich-Kwong equation of state. Chem. Eng. Sci. 27 (6): 1197–1203. http://dx.doi.org/10.1016/0009-2509(72)80096-4
- ↑ 11.0 11.1 11.2 11.3 Schou Pedersen, K., Skovborg, P., and Roenningsen, H.P. 1991. Wax precipitation from North Sea crude oils. 4. Thermodynamic modeling. Energy Fuels 5 (6): 924-932. http://dx.doi.org/10.1021/ef00030a022
- ↑ 12.0 12.1 12.2 Pedersen, W.B., Hansen, A.B., Larsen, E. et al. 1991. Wax precipitation from North Sea crude oils. 2. Solid-phase content as function of temperature determined by pulsed NMR. Energy Fuels 5 (6): 908-913. http://dx.doi.org/10.1021/ef00030a020
- ↑ Mei, H., Kong, X., Zhang, M. et al. 1999. A Thermodynamic Modelling Method for Organic Solid Precipitation. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 3-6 October. SPE-56675-MS. http://dx.doi.org/10.2118/56675-MS
- ↑ Nichita, D.V., Goual, L., and Firoozabadi, A. 1999. Wax Precipitation in Gas Condensate Mixtures. Presented at the SPE Annual Technical Conference and Exhibition, Houston, Texas, USA, 3-6 October. SPE-56488-MS. http://dx.doi.org/10.2118/56488-MS
- ↑ 15.0 15.1 15.2 15.3 Schou Pedersen, K. 1995. Prediction of Cloud Point Temperatures and Amount of Wax Precipitation. SPE Prod & Oper 10 (1): 46-49. SPE-27629-PA. http://dx.doi.org/10.2118/27629-PA
- ↑ 16.0 16.1 Hansen, J.H., Fredenslund, A., Pedersen, K.S. et al. 1988. A thermodynamic model for predicting wax formation in crude oils. AIChE J. 34 (12): 1937-1942. http://dx.doi.org/10.1002/aic.690341202
- ↑ Flory, P.J. 1953. Principles of Polymer Chemistry. Ithaca, New York: Cornell University Press.
- ↑ 18.0 18.1 18.2 18.3 18.4 18.5 Erickson, D.D., Niesen, V.G., and Brown, T.S. 1993. Thermodynamic Measurement and Prediction of Paraffin Precipitation in Crude Oil. Presented at the SPE Annual Technical Conference and Exhibition, Houston, 3-6 October. SPE-26604-MS. http://dx.doi.org/10.2118/26604-MS
- ↑ 19.0 19.1 Won, K.W. 1986. Thermodynamics for solid solution-liquid-vapor equilibria: wax phase formation from heavy hydrocarbon mixtures. Fluid Phase Equilib. 30 (0): 265-279. http://dx.doi.org/10.1016/0378-3812(86)80061-9
- ↑ 20.0 20.1 20.2 Lira-Galeana, C., Firoozabadi, A., and Prausnitz, J.M. 1996. Thermodynamics of wax precipitation in petroleum mixtures. AIChE J. 42 (1): 239-248. http://dx.doi.org/10.1002/aic.690420120
- ↑ Peng, D.-Y. and Robinson, D.B. 1976. A New Two-Constant Equation of State. Industrial & Engineering Chemistry Fundamentals 15 (1): 59–64. http://dx.doi.org/10.1021/i160057a011
- ↑ 22.0 22.1 22.2 Pan, H., Firoozabadi, A., and Fotland, P. 1997. Pressure and Composition Effect on Wax Precipitation: Experimental Data and Model Results. SPE Prod & Oper 12 (4): 250-258. SPE-36740-PA. http://dx.doi.org/10.2118/36740-PA
- ↑ 23.0 23.1 Ungerer, P., Faissat, B., Leibovici, C. et al. 1995. High pressure-high temperature reservoir fluids: investigation of synthetic condensate gases containing a solid hydrocarbon. Fluid Phase Equilib. 111 (2): 287-311. http://dx.doi.org/10.1016/0378-3812(95)02771-6
- ↑ 24.0 24.1 Coutinho, J.A.P. 1998. Predictive UNIQUAC: A New Model for the Description of Multiphase Solid−Liquid Equilibria in Complex Hydrocarbon Mixtures. Ind. Eng. Chem. Res. 37 (12): 4870-4875. http://dx.doi.org/10.1021/ie980340h
- ↑ 25.0 25.1 Coutinho, J.A.P., Andersen, S.I., and Stenby, E.H. 1995. Evaluation of activity coefficient models in prediction of alkane solid-liquid equilibria. Fluid Phase Equilib. 103 (1): 23-39. http://dx.doi.org/10.1016/0378-3812(94)02600-6
- ↑ 26.0 26.1 26.2 26.3 26.4 Coutinho, J.A.P. and Stenby, E.H. 1996. Predictive Local Composition Models for Solid/Liquid Equilibrium in n-Alkane Systems: Wilson Equation for Multicomponent Systems. Industrial Engineering Chemistry Research 35: 918.
- ↑ 27.0 27.1 27.2 Coutinho, J.A.P. 2000. A Thermodynamic Model for Predicting Wax Formation in Jet and Diesel Fuels. Energy Fuels 14 (3): 625-631. http://dx.doi.org/10.1021/ef990203c
- ↑ Pauly, J., Daridon, J.-L., Coutinho, J.A.P. et al. 2000. Prediction of solid–fluid phase diagrams of light gases–heavy paraffin systems up to 200 MPa using an equation of state–GE model. Fluid Phase Equilib. 167 (2): 145-159. http://dx.doi.org/10.1016/S0378-3812(99)00316-7
- ↑ Won, K.W. 1986. Thermodynamics for solid solution-liquid-vapor equilibria: wax phase formation from heavy hydrocarbon mixtures. Fluid Phase Equilib. 30 (0): 265-279. http://dx.doi.org/10.1016/0378-3812(86)80061-9
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Thermodynamics and phase behavior