Characterization Index for Vacuum Residua and Their Subfractions

Subfractions. Tie-Pan Shi,1 Zhi-Ming Xu, Min Cheng, Yun-Xiang Hu, and Ren-An Wang. State Key Laboratory of Heavy Oil Processing, University of Petrole...
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Energy & Fuels 1999, 13, 871-876

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Characterization Index for Vacuum Residua and Their Subfractions Tie-Pan Shi,1 Zhi-Ming Xu, Min Cheng, Yun-Xiang Hu, and Ren-An Wang State Key Laboratory of Heavy Oil Processing, University of Petroleum, Beijing 102200, China Received November 30, 1998. Revised Manuscript Received May 5, 1999

Supercritical fluid extraction and fractionation (SFEF) has been developed to separate eight Chinese and Mideast petroleum vacuum residua. Elemental analysis, average molecular weight, and SARA (saturates, aromatics, resins, and asphaltenes) determinations were performed on the vacuum residua and their subfractions. Based on an analysis of the collected data, a characteristic index, KH, consisting of H/C ratio, molecular weight, and density is developed. The index is used to correlate properties such as carbon residue and saturates percentages. The reference data on thermal cracking, catalytic cracking, and heavy oil pyrolysis proved the validity of the new index. Thus, the KH index is useful in the classification and evaluation of heavy oil and has the potential for extended application.

Introduction The most serious challenge for Chinese refiners may be in the processing of heavy oils. Vacuum residues present a particular problem because they comprise 40 to 50 w/w% of crude oils.1 However, the need to upgrade heavy oils, so as to utilize the resource to the maximum possible extent, calls for an in-depth understanding of heavy oil chemistry. Although many studies on chemical composition and conversion have been published in past decades, some fundamental questions remain unresolved because vacuum residues contain a wide spectrum of both hydrocarbons and nonhydrocarbons with high molecular weights and boiling points.1 Liquid chromatography is routinely used to separate heavy oils according to their solubility or polarity. A major drawback to this approach is that the amount of each subfraction produced is insufficient to study its conversion performance. Also, an inherent weakness associated with high vacuum distillation is that it cannot deeply cut vacuum residua. A supercritical fluid extraction and fractionation (SFEF) method has been used to cut deeply into vacuum residua to provide a number of samples in sufficient amounts to measure the variation in properties such as elemental composition, average molecular weight, SARA (saturates, aromatics, resins, and asphaltenes), etc. The average boiling point of the heavy oils was estimated with a prediction model based on their properties. These boiling points are used to calculate a characterization factor, the Watson K or UOP K, in the higher boiling range. The validity of extending the use of the Watson K index to heavy oils is assessed. Thermal cracking and catalytic cracking performance of some of the SFEF narrow cuts, or mixes of those * To whom correspondence should be addressed. E-mail: [email protected]. (1) Cheng, Z.-G., Ed. Heavy Oil Processing Technology; China Petrochemical Press: Beijing, 1994 (in Chinese).

narrow cuts, have also been studied in our laboratory. A combinatorial analysis of the accumulated property/ reaction data from heavy oil research in this laboratory has led to the proposal of a new characterization index for vacuum residues and their subfractions. Experimental Section The principle and operation of SFEF have been described in previous papers.2,3 n-Pentane, with a critical temperature of 196.6 °C and a critical pressure of 33.3 atm, was used as the supercritical fluid to separate vacuum residua. In summary, about 1000 g of vacuum residuum was charged into the extractor (3.5 liters volume) and brought into contact with the supercritical fluid. Based on our experience, the same relatively severe operating conditions were applied to all of the vacuum residua to provide a common basis for comparison. The temperature in the extractor was maintained at 240 °C, while the fractionation section had a temperature gradient ranging from 240 °C at the bottom to 250 °C at the top. The pressure was 4.0-12.0 MPa with a gradient of 1.0 MPa/hr. About 50 g of each narrow cut can be collected with increasing pressure. In this work, Daqing, Dagang, Gudao, Shengli, Huabei, Liaohe, Oman, and Saudi Arabian vacuum residua were separated into 14-17 narrow cuts by SFEF. Total yields from each sample were 87.8, 75.4, 73.0, 71.7, 84.5, 77.7, 87.1, and 80.2%, respectively. For reactivity studies, the residues were cut into two portions by SFEF, i.e., DAO (deasphaltened oil) and DOA (deoiled asphalt). DAO yields were about 30, 40, 50, 60 w/w%. The characteristic properties, such as density and Conradson carbon residue (CCR), of each narrow fraction were determined. The elemental analysis was carried out on a Perkin-Elmer CHNS/O analyzer 2400 (Perkin-Elmer Co., USA), while average molecular weights were measured on a Knauer vapor pressure osmometer (Knauer Instruments, Germany). The SARA analysis involved separation of maltenes by precipitation with n-heptane. The maltenes were then (2) Wang, R.-A.; Bai, S.; Fan, Y.-H.; Hu, Y.-H.; Li, H.; Zhou, M.-L. Chinese Patent, ZL 93117577.1, 1993. (3) Xu, Z.-H. MS Thesis, University of Petroleum, Beijing, 1994.

10.1021/ef980258z CCC: $18.00 © 1999 American Chemical Society Published on Web 06/26/1999

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Figure 1. Average molecular weights (VPO method) versus midpoint yields for narrow cuts from eight different vacuum residua.

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Figure 3. Densities versus midpoint yields for narrow cuts from eight different vacuum residua.

ratios (data not included here), and relatively high contents of aromatics or resins. We can conclude that separation by SFEF produces narrow fractions that change progressively with increasing cumulative yield. However, the fractions from each sample include a wide range of properties, and the fractions from different residua are significantly different. Consequently, it is reasonable to extend the results derived from the vacuum residua and their narrow fractions studied here to other vacuum residua or heavy oils. Watson K for Vacuum Residua. Watson K,5 or UOP K, is defined as 3

1.216xTb K) SG

Figure 2. H/C atomic ratios versus midpoint yields for narrow cuts from eight different vacuum residua. separated chromatographically on an alumina column to produce saturate, aromatic, and resin fractions.

Results and Discussion Properties of SFEF Narrow Cuts. Average molecular weights, densities, and H/C atomic ratios were determined for narrow fractions from eight heavy oil samples. The results are summarized in Figures 1-3. From this information we see that the narrow fractions with higher cumulative yields have higher molecular weights, higher densities, and lower H/C atomic ratios. The trends in property variation agree well with previous work.4 Exceptions to the trends are the well-known differences between Chinese oils and those from other sources.1 For the latter oils these include higher nickel and vanadium contents, higher vanadium-to-nickel (4) Shi, T.-P.; Hu, Y.-X.; Xu, Z.-M.; Su, T.; Wang, R.-A. Ind. Eng. Chem. Res. 1997, 36, 3988-3992.

(1)

where Tb (K) is the average boiling point and SG the specific gravity at 15.6/15.6 °C. For light oil fractions, Tb can be measured by both ASTM or TBP distillation methods. However, it is difficult to measure boiling points above 700 °C. Therefore, calculations of the Watson K index for vacuum residua depend, to a large extent, on an appropriate boiling point prediction model. Pedersen,6 Riazi and Daubert,7 and Xu3 have proposed several models for the prediction of average boiling points. A common feature of these three models is that the average molecular weight terms are raised to the power of about 0.35, indicating a similar contribution to Tb in each case. After evaluation the Xu model is adopted in this paper:

Tb ) 79.23M0.3709d0.1326

(2)

where M is the average molecular weight (g/mol) and d the density at 20 °C (g/cm3). The applicability of this model has been confirmed in subsequent work. Watson K values for vacuum residua can thus be calculated by substituting Tb from eq 2 into eq 1. (5) Watson, K. M.; Nelson, E. F. Ind. Eng. Chem. 1933, 25(8), 880887. (6) Pedersen, K. S.; Fredenslund, A.; Thomassen, P. Properties of Oils and Natural Gases; Gulf Publishing Co.: Houston, 1989. (7) Riazi, M. R.; Daubert T. E. Hydrocarbon Process. 1980, 59(3), 115-116.

Vacuum Residua Characterization Index

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Table 1. Properties of Three SFEF Fractions with Similar Watson K Values SFEF fraction

Daqing-2

Dagang-16

Gudao-15

Watson K H/C atomic ratio molecular weight density (20 °C), g/cm3 saturates, wt % aromatics, wt % resin, wt %

12.88 1.85 689 0.9058 73.48 20.64 5.88

12.87 1.57 1484 1.0009 2.73 45.41 51.86

12.85 1.55 1678 1.0185 0.94 36.53 62.53

Chemical composition and structure determine the physicochemical properties of heavy oils. Generally, an assessment of the characteristic nature of a heavy oil requires the combination of physicochemical properties such as elemental analyses, molecular weight, SARA contents, and structural parameters. The Watson K characterization factor provides a good measure of a crude’s quality classification and its use is common practice for commercial purposes. Light oils or crudes with similar properties have almost the same Watson K values. Consequently, the Watson K is widely used for the classification and property correlation of both crude and light oils. This should also be a criterion in the derivation of a new characterization index for heavy oils. Provided that good estimates of the Watson K index can be established for vacuum residua and their subfractions, then those narrow fractions with close Watson K values should have similar bulk properties. However, in our present work we did not find this to be true, as shown in Table 1. Therefore, we can say that the Watson K index is not suitable for the characterization and classification of vacuum residua. New Characterization Index KH. As Watson K values are not suitable for heavy oils, a reliable characterization index is needed to give an explicit measure for quality assessment and/or property correlation and prediction for heavy oils. After several trials, a characterization index composed of several representative properties is shown to be better than one using a single specific property. In proposing a new characterization index for vacuum residua we continue the rational use of the power 1/3 of Tb in eq 1. Thus according to eq 2,

Figure 4. KH versus CCR values for SFEF narrow cuts from eight vacuum residua.

(3)

Figure 5. KH versus saturate percentages for various vacuum residua and their subfractions.

Nevertheless, we attribute the failure of Watson K for subfractions of vacuum residua to the lack of a parameter which is representative of its chemical composition. Thus, we incorporate the H/C atomic ratio, an important property for heavy oil, into the proposed formula for the new characterization index. With H/C atomic ratio, molecular weight, and density, the final expression for the characterization index for heavy oils (KH) was chosen to be

with Watson K values which are larger than 10 for most crudes. The lighter narrow cuts have higher KH values, and those with similar overall properties, surely not one single property, are proved to have close KH values. KH vs Properties. Carbon residue of a heavy oil is usually used to demonstrate the propensity for coke formation in thermal and catalytic cracking reactions. Figure 4, a plot of KH versus CCR values for eight series of SFEF narrow fractions, shows that KH can be correlated to CCR value. By regression analysis we can determine the prediction model for CCR:

Tb1/3 ∝ M0.1236d0.0442 ∝ M0.1236 (d0.0442 ≈ 1)

H/C KH ) 10 0.1236 M d

(4)

The coefficient 10 in eq 4 is introduced to adjust the values of KH to an appropriate range between 5 and 10. The values of KH are monotonic for a series of narrow cuts in accordance with the variation of their bulk properties. Also, its range shows a seeming continuation

CCR(%) ) 2.451 KH2 - 44.10 KH + 200.0

(5)

where the average absolute deviation (AAD) is 1.2%. Surprisingly, we also found a good correlation between KH and the percentages of saturates. Figure 5 shows KH versus percentage of saturates for Daqing, Dagang, Gudao, Shengli, Huabei, and Liaohe vacuum residua and their subfractions. The 128 data points

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Figure 7. Yields of gasoline,