Page 203 - Characterization and Properties of Petroleum Fractions - M.R. Riazi
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QC: —/—
                                      T1: IML
               P2: KVU/KXT
  P1: KVU/KXT
                        AT029-Manual-v7.cls
                                           June 22, 2007
                                                        21:30
  AT029-04
            AT029-Manual
                                              4. CHARACTERIZATION OF RESERVOIR FLUIDS AND CRUDE OILS 183
                                TABLE 4.19—Sample calculations for prediction of distribution of properties of the C 7+
                                                       fraction in Example 4.13.
                                     x wi  x cw   T bi ,K  SG i   x vi   x cv   M i    x mi    I i
                              No.    (1)    (2)    (3)    (4)     (5)    (6)    (7)    (8)    (9)
                              1     0.05  0.025   353.8  0.720   0.053  0.026  91.4   0.065  0.244
                              2     0.05  0.075   359.3  0.730   0.052  0.079  93.9   0.063  0.247
                              3     0.05  0.125   364.3  0.735   0.052  0.131  96.3   0.062  0.249
                              i     ...    ...     ...    ...     ...    ...    ...    ...    ...
             3. Choose 20 (or more) arbitrary cuts for the mixture with  T o = 350 K, A T = 0.1679, and B T = 1.2586. An initial guess
               equal weight (or volume) fractions of 0.05 (or less). Then  value of SG o = 0.7 is used to calculate A SG and SG distribu-
               determine T bi for each cut from Eq. (4.56) and coefficients  tion coefficients. Now we divide the whole fraction into 20
               from step 2.                                       cuts with equal weight fractions as x wi = 0.05. Similar to cal-
             4. Guess an initial value for SG o (lowest value is 0.59).  culations shown in Table 4.17, x cw is calculated and then for
             5. Calculate 1/J from Eq. (4.80) using SG o and SG 7+ . Then  each cut values of T bi and SG i are calculated. From these two
               calculate A SG from Eq. (4.79) using Newton’s method or  parameters M i and I i are calculated by Eqs. (2.56) and (2.115),
               other appropriate procedures. If original TBP is in terms  respectively. From x wi and M i mole fractions (x mi ) are calcu-
               of x cv , then Eq. (4.76) should be used to determine A SG in  lated. Sample calculation for the first few points is given in
                                                                  Table 4.19 where calculation continues up to i = 20. The co-
               terms of x cv.
             6. If original TBP is in terms of x cv , find SG distribution from  efficients of Eq. (4.56) determined from data in Table 4.19
               --`,```,`,``````,`,````,```,,-`-`,,`,,`,`,,`---
               Eq. (4.56) in terms of x cv . Then use SG to convert x v to x w  are given in Table 4.20. In this method parameter ε 1 = 0.0018
               through Eq. (1.16).                                (step 13), which is less than 0.005 and there is no need to
             7. Using values of SG and T b for each cut determine values  re-guess SG o . In this set of calculations since initial guess for
               of M from Eq. (2.56).                              SG o is the same as the actual value only one round of cal-
             8. Use values of M from step 7 to convert x w into x m through  culations was needed. Coefficients given in Table 4.20 have
               Eq. (1.15).                                        been used to generate distribution for various properties and
             9. From data calculated in step 8, find molar distribution by  they are compared with predicted values from Method A as
               estimating coefficients M o , A M , and B M in Eq. (2.56).  well as actual values given in Table 4.11. Results are shown in
            10. Calculate value of I for each cut from T b and SG through  Figs. 4.23 and 4.24 for prediction of M and T b distributions.
               Eq. (2.115) or (2.116).                            Methods A and B predict similar distribution curves mainly
            11. Find coefficients I o , A I , and B I (set B I = 3) from data ob-
               tained in step 10. Set I 1 = I o .
            12. From SG o assumed in step 4 and M o determined in step 9,  TABLE 4.20—Estimated coefficients of Eq. (4.56)
                                                                                for the C 7+ of Example 4.13.
               estimate I o through Eq. (4.94). Set I 2 = I o .       Property            A        B
            13. Calculate ε 1 =|(I 2 − I 1 )/I 1 |.                   M        90 P o  0.3324    1.096   Type of x c
                                                                                                           x cm
            14. If ε 1 ≥ 0.005 go back to step 4 by guessing a new value for  T b  350  0.1679   1.2586    x cw
               SG o .If ε 1 < 0.005 or it is minimum go to step 15.   SG        0.7    0.0029    3.0       x cw
            15. Print M o , A M , B M ,SG o , A SG , T o , A T , B T , I o , A I , and B I .  I  0.236  7.4 × 10 −4  3.6035  x cv
            16. Generate distributions for M, T b , SG, and n 20 from
               Eq. (4.56).
                                                                        300
            The following example shows application of Method B to find             Experimental
            property distribution of a C 7+ when data on TBP distillation,         Method A
            M 7+ and SG 7+ are available.                               250        Method B

            Example 4.13—For the C 7+ of Example 4.7, assume that       200
            T b distillation curve is available, as given in columns 3 and
            5 in Table 4.11. In addition assume that for this sample  Molecular Weight, M
            M 7+ = 118.9 and SG 7+ = 0.7597 are also available. Using the  150
            method described above (Method B) generate M, T b , SG, and
            I distributions. Graphically compare prediction of various
            distributions by Methods A and B with actual data given in
                                                                        100
            Table 4.11.
            Solution—Similar to Example 4.12, step-by-step procedure     50
            described under Method B should be followed. Since data on     0      0.2    0.4     0.6     0.8     1
            distillation are given in terms of weight fractions (column 3 in
            Table 4.11) we choose weight fraction as the reference for the     Cumulative Mole Fraction, x
            composition. From data on T bi versus x wi distribution coeffi-                            cm
            cients in Eq. (4.56) can be determined. This was already done  FIG. 4.23—Prediction of molar distribution in Examples
            in Example 4.7 and the coefficients are given in Table 4.13 as:  4.12 and 4.13.














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