Asphaltene precipitation in crude oils: Theory and experiments

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Figure 8. Prediction of asphaltene precipitation with n-alkanes for C1 tank oil sample. accurate because of the viscosity of the oil–solvent solutions. However, accuracy improves at the higher solvent ratios. Comparison between Sutherland and SW potentials The model parameters were fitted from the n-heptane titration data of oil C1, for the Sutherland and SW potentials. The corresponding fitted parameters are given in Table 9. In Figure 6, the n-heptane titration curves for the C1 crude oil, calculated using both interaction potential models, are compared with the experimental data. In both cases, the calculated fractional precipitation is within the 13% error of the experimental value. According to these results, the use of any of these interaction potential models does not represent any appreciable difference in the representation of asphaltene precipitation. This result is explained by the fact that the association contribution to the total free energy dominates over the mean-attractive energy contribution. Thus, the model results that are presented were obtained using the Sutherland potential. Modeling the effect of the medium properties In titration experiments, the change of the medium or solvent properties is attributed to the dilution of the oil with a diluent (that is, the n-alkane). As the carbon number of the normal alkane increases, its density and dielectric constant increase as well (see Table 2). Considering a precipitant-to-oil ratio of 50 mL/g, Table 10 shows that the Hamaker constant of the medium increases as the carbon number of the precipitant increases, and that the screening effect over interactions of solutes becomes stronger, decreasing the energy parameter of the attractive potential ( AmA ) and the amount of precipitated material, according to experimental results (see Figure 7). The solvent properties directly affect the mean-attractive energy term in the monomer contribution to the total Helmholtz free energy a 1 . In our SAFT-VR EOS approach, the association free energy contribution also depends on a 1 ; then the conditions that determine the amount of precipitated material are also modified. Prediction of asphaltene precipitation with n-alkanes The n-pentane, n-octane, and n-dodecane titration curves for the crude oil C1 predicted with SAFT-VR, using the Sutherland interaction potential and the parameters fitted from the n-heptane titration curve alone (Table 9), are compared with the experimental data. The predicted fractional precipitation agrees well with the experimental values for the n-pentane titration curve only at low Figure 9. Prediction of the asphaltene precipitation with n-alkanes for Y3 tank oil sample. AIChE Journal October 2004 Vol. 50, No. 10 2563
Table 11. Experimental Onset Pressures of Live-Oil Samples T P (bar) (K) C1 Y3 413.15 345.10 372.18 393.15 360.45 455.56 363.15 379.85 354.15 474.63 348.15 386.02 335.15 600.19 bar 1 10 5 Pa dilution. For n-nonane and n-dodecane the prediction is much better for high-dilution ratios than for low-dilution ratios. In all cases the predicted fractional precipitation at dilution ratios 5 mL/g are within the 10% error of the experimental values. Figure 8 shows these comparisons in detail. To test the predictive power of our thermodynamic model in a different crude oil, the prediction of a different set of experimental titration data from the Y3 stock-tank oil was studied. The predicted titration curves for the Y3 tank oil are given in Figure 9. The values of the model parameters in this case were the same fitted values used for oil C1, except for the association energy parameters AA and AR , whose values were obtained from titration data of oil Y3 with n-heptane. Values of the new parameters are AA /k 2062.21 K and AR /k 2359.43 K. No other assumptions or parameter modifications were used. The predicted precipitation curves for oil Y3 resulted within 10% error of the experimental data for precipitant/oil ratios 10. However, for lower ratios, there are larger deviations from the experimental values, even though the model reproduces the decrease of the precipitation as the carbon number of the precipitant increases. As mentioned earlier, for the prediction of the precipitation in oil Y3, it was not necessary to refit the parameters related to the mean-attractive energy (the Hamaker constants and the range of the mean-force potentials). These results can be explained in terms of the similar properties and composition of C1 and Y3 crude oils and the use of the same values for the asphaltene and resin properties (Table 1), considering that both oils are produced in the same geographical location. However, it is more likely to be a consequence of the fact that the asphaltene precipitation upon mixing crude with normal alkanes is controlled mainly by associating interactions. Then, the parameters of the attractive meanforce potential have a secondary role in the modeling of the precipitation, although it is important to stress that in the SAFT-VR EOS approach the associating and mean-attractive energies are actually coupled by the perturbation approximation followed for the calculation of the radial distribution function at the contact value (see Appendix A). Asphaltene precipitation at high pressure Table 11 shows the onset pressure points of asphaltene precipitation measured at four different temperatures for the live oils C1 and Y3. These points belong to the upper boundary of the APE. It is observed that as the temperature increases, the pressure at the onset point diminishes, reflecting an increment of the asphaltene solubility with temperature. The increased solubility means that the onset of asphaltene precipitation requires a greater perturbation of the solvent or medium conditions, such as the oil density, which implies greater pressure depletion with respect to the reservoir condition. To model asphaltene precipitation in a reservoir fluid at certain T and P conditions, the vapor–liquid equilibrium calculation of the reservoir fluid is first performed using a cubic equation of state, to obtain the composition and fluid properties of the liquid phase at equilibrium. Then, using the asphaltene– resin–oil model system described before, the phase-stability analysis is applied to find out the onset of asphaltene precipitation. When asphaltene precipitation appears, the amount of precipitated material is calculated by solving the liquid–liquid equilibrium equations. Calculation of Medium Properties. Following Wu et al. (2000), the volume-shifted Peng–Robinson EOS (Peneloux et al., 1982; Peng and Robinson, 1976) was used to model the vapor–liquid–equilibrium to obtain the density and composition of the liquid phase. Recommended values for the binary Figure 10. Comparison between experimental and predicted APE for live oil C1. 2564 October 2004 Vol. 50, No. 10 AIChE Journal
Page 1 and 2: THERMODYNAMICS Asphaltene Precipita
Page 3 and 4: Table 1. Properties of Dead Oil Sam
Page 5 and 6: Mw Table 4. Characterization of Pse
Page 7 and 8: Figure 4. Pressure vs. displaced vo
Page 9 and 10: parameter can also be estimated fro
Page 11: Table 10. Effect of the Carbon Numb
Page 15 and 16: Table 14. Effect of the Medium Dens
Page 17 and 18: Pressures: Calculation of Partial M
Page 19: The effective packing fraction in E

Asphaltene precipitation in crude oils: Theory and experiments

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