Reactivity and Comprehensive Kinetic Modeling of Deasphalted

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Reactivity and Comprehensive Kinetic Modeling of Deasphalted Vacuum Residue Thermal Cracking Fredy A. Cabrales-Navarro, and Pedro Rafael Pereira-Almao Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.6b02544 • Publication Date (Web): 22 Feb 2017 Downloaded from http://pubs.acs.org on February 24, 2017

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Reactivity and Comprehensive Kinetic Modeling of Deasphalted Vacuum Residue Thermal Cracking Fredy A. Cabrales-Navarro* and Pedro Pereira-Almao Department of Chemical and Petroleum Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive N.W., Calgary, AB T2N 1N4 , Canada * Corresponding author ([email protected])

ABSTRACT Upgrading and Refining of Heavy Oil and Bitumen has become a costly practice in the last decades, creating a need for new processes to appropriately convert these heavy feedstocks into lighter and more valuable materials. Solvent Deasphalting (SDA) is a carbon rejection process where asphaltenes are removed from the oil using a paraffinic solvent, producing a lighter deasphalted oil (DAO) stream that can be further upgraded without the limitations of asphaltenes instabilities. In this work, upgrading via thermal cracking of deasphalted vacuum residue was assessed in a bench scale pilot plant equipped with an up-flow open tubular reactor. Two different feedstocks were evaluated: recycled and virgin DAO. Reactivity experiments were carried out at temperatures within the interval 380-423 °C and Liquid Hourly Space Velocities (LHSV) of 0.25-3 h-1. The effects of operating pressure and steam partial pressure on thermal crackability of DAO were also evaluated not having significant effect within the 150-300 psig range. Experimental results showed increased reactivity of virgin DAO compared to recycled DAO as well as better quality and higher selectivity to more valuable products. A lumped kinetic modeling including asphaltenes generation was evaluated. Different scenarios were assessed to incorporate chemical considerations within the complex lumped kinetic model developed, which

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have significant effect on the kinetic parameters as well as the possible interpretation of the results. Overall, typical behavior was observed for thermal cracking with global activation energies of 241 kJ/mol 226 kJ/mol for recycled and virgin DAO (560 °C+) respectively. Good fitting of the model with experimental data with relative errors around 7 % and clear kinetic relevance of the asphaltenes generation reaction during thermal cracking was highlighted. Keywords: virgin DAO, recycled DAO, Asphaltenes, Lump, Thermal Cracking. 1. INTRODUCTION Asphaltenes, a group of heavy hydrocarbons found in larger proportions in heavy and extraheavy oils, defined by their insolubility in n-paraffinic solvents such as pentane or hexane and solubility in aromatics like toluene are directly related to the increase in viscosity and density of the oil.1 For this reason, the use of solvent deasphalting (SDA) to separate the asphaltenic compounds has become practical in the heavy oil upgrading industry. The presence of asphaltenes not only limits the application of catalytic processes for further upgrading of the oil due to catalyst poisoning, but also the achievement of increased conversions in conventional processes such as thermal cracking (TC) due to their instability when submitted to moderate severity conditions.2,3 In this way, there is a new window of opportunities for new technologies for deep conversion of deasphalted oil (DAO) streams into lighter and more valuable compounds. These potential developments need appropriate kinetic models that would allow the simulation of said processes on an industrial scale. This valuable information is abundant for hydrocracking4-6 and conventional thermal cracking7-10 using hydrocarbon fractions such as Vacuum Residue (VR), but little information is available in the open literature for DAO thermal cracking. As an example, analyzing the upgrading schemes shown in Figure 1, which is based on a combination of SDA/TC with recycling of the thermally cracked DAO commercially


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known as the OrCrudeTM process11 when operated in a recycle mode, it is crucial to model the thermal cracking operation and to accurately estimate the amount of valuable products, such as Atmospheric Gasoil (AGO) and VGO. Moreover, the amount of pitch obtained, which is a combination of pentane insoluble asphaltenes and resins characterized by having a lower economic value and being difficult to process, would depend not only on the amount of asphaltenes originally present in the bitumen, but on the amount of asphaltenes generated from the thermal cracking process. For this reason, it is essential to predict the amount of these heavy compounds generated in order to have an accurate estimation of the pitch yield in the upgrading scheme. For the kinetic modelling of DAO upgrading via thermal cracking, a traditional lumping technique in which the hydrocarbon is divided into lumps of fractions defined by their boiling point is proposed. Several authors have used this approach for thermal cracking of vacuum residue using lumping schemes that can range from a simple two lumps model such as the work of Del Bianco et al.12 to more complex reaction pathways involving 5 or 6 different lumps such as investigations by Singh et al.13 or Mohaddecy and Sadighi14 respectively. Kataria et al.10 and Singh et al.9 have presented a very detailed chronological summary about kinetic modeling approaches for visbreaking of residual feedstocks. On the other hand, these types of lumping kinetic models have also been successfully used for Hydrocracking and Catalytic Steam Cracking (CSC) of vacuum residue. Sanchez, et al.5 followed this approach for moderate hydrocracking of Maya heavy crude with a Ni/Mo catalyst. Also, it was successfully implemented by Puron et al.4 for hydrocracking of a vacuum residue fraction from Maya heavy oil using the catalytic matrixes NiMo/Al2O3, and NiMo/Al2O3-Cr. Furthermore, this methodology has been used for kinetic modeling bitumen hydroprocessing near reservoir


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conditions using ultradispersed catalysts.15-17 It was also preliminarily used by Fathi and PereiraAlmao18 for thermal cracking and catalytic steam cracking of Arab light vacuum residue (ALVR) at high space velocities using ultra-dispersed catalysts under very similar conditions to the ones used in this work. A common flaw of most mentioned models is that in the considered pathways, the formation of coke precursors (asphaltenes) is not considered. Asphaltenes are known to promote the formation of insoluble materials such as coke and also to increase the yield of gases. Thus, their incorporation in the model is of relevance considering that they seriously affect the conversion limit of the cracking process; most models assume working conditions under which those reaction paths are negligible. For bituminous oils, it is not appropriate to neglect the influence of asphaltenes on the reaction scheme, since there are considerable amounts of them within the feedstock. Even for deasphalted oil fractions, where the majority of the asphaltenes has been removed, their generation during the reaction is significant. As a result, they have a relevant effect on the kinetic model. This work targets the development of a multi-lumps kinetic model that was progressively analyzed to reduce to 8-lumps incorporating the formation of asphaltenes during thermal cracking of recycled and virgin DAO obtained from a bitumen upgrading facility located in Northern Alberta, Canada. The main objective of the work is to gain understanding about the reactivity of DAO thermal cracking and the kinetics of formation of pentane insoluble asphaltenes when included as a separate lump in the kinetic model, an approach not reported in the open literature thus far. In addition, this work aims to create a more robust practical model differentiating the reactivity of vacuum gas oil by splitting it into heavy vacuum gas oil (HVGO) and light vacuum gas oils (LVGO), effective streams in most industrial vacuum distillation units.


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Using a similar reasoning, the distillates lump was split into diesel and kerosene instead of the simplified lumping as distillates. Analyzing the results of our modeling it was found that a reduced number of kinetic constants are really needed to express the kinetic process. For instance the lighter lumps diesel, kerosene and naphtha do not react to lighter products at the evaluated conditions. In addition, the effect of varying total operating pressure and steam partial pressure on the DAO reactivity was assessed. 2. EXPERIMENTAL METHODS 2.1. Experimental Setup. The reactivity tests were carried out in an experimental setup equipped with an up-flow open tubular reactor that resembles a conventional thermal cracking unit. A general scheme of the reactivity test unit is shown in Figure 2. The reactivity test unit is composed of five sections: the feed section, reaction section, hot separation section, cold separation section, and finally the gas release, depressurization and analysis section. The feed section is equipped with a Teledyne ISCO series 500D dual-pump continuous flow system with dual pneumatic air-valves controlled by a Series D Controller, which refills one pump while the other one is delivering DAO. Also, there is a Shimadzu LC20AD high performance liquid chromatography pump for water injection. Feed streams were mixed inline before entering the reaction zone, which comprises an up-flow open tubular reactor with a volume of 103.46 mL, operated at constant temperature and pressure, and equipped with an Omega custom 7 sensing points thermocouple profile probe. The products coming out from the reaction zone go to a hot separator in which the water, gases, and a fraction of the lightest hydrocarbons are separated from the product by keeping the separator at a constant temperature (mostly 250 °C). The separated gaseous stream is then passed through a condenser in order to


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liquefy the light hydrocarbons and water, and the whole stream is sent to the cold separation section where gases are separated from the liquid product. Finally, gases coming out from the cold separation zone passed through a back pressure valve, which maintains the operating pressure at the given set point, and the gas stream is sent to gas release and analysis. In this zone, the exiting gas stream can be directed to mass flow measurements, GC analysis or directly to the gas exhaust. Gas stream is first sweetened by bubbling in an aqueous potassium hydroxide (KOH) trap and then it is either vented or sent to gas flow measurement in a Shinagawa W-NK0.5 wet gas meter (WTM). The other mode of operation is to flow the stream through a gas chromatograph (GC) for gas composition analysis, followed by gas sweetening in a similar KOH trap and finally the stream is vented. 2.2. Experimental Plan Two industrial deasphalted vacuum residues obtained from a bitumen upgrading facility located in Northern Alberta, Canada were characterized: virgin DAO and recycled DAO. Virgin DAO comes from direct solvent deasphalting of vacuum residue (560ºC+) using pentane, when the upgrading scheme is operated in once-through mode as shown in Figure 1. On the other hand, recycled DAO is the feedstock obtained when the upgrading scheme is in recycle mode (refer to Figure 1). In this case, deasphalted oil is kept on a thermal cracking/separation loop in such a way that only the lighter hydrocarbons are produced (Gas, Naphtha, Kerosene, Diesel, LVGO and HVGO), and the DAO (560ºC+) is kept in the thermal cracking loop. As there is always fresh bitumen coming in, the DAO stream in this mode of operation would be composed of a portion of virgin or unprocessed hydrocarbons and a majority of material that has been cracked or partially converted several times. Characteristics of both feedstocks are presented in Table 1.


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Thermal cracking in the presence of 5 % wt. steam and operating pressure within the 260 to 400 psig range has been carried out in the Catalysis for Bitumen Upgrading Research Facility at the University of Calgary for different feedstocks such as Arab light vacuum residue19 and Athabasca vacuum gas oil20 with satisfactory results that allow to apply a similar methodology for a residual deasphalted oil feedstock. A total of 12 conditions were evaluated for recycled DAO thermal cracking experiments required for the kinetic modeling, consisting of three different LHSVs at four different temperatures: 380, 409, 416 and 423 ºC. The LHSV set at each temperature were chosen in such a way that the most severe conditions were as close as possible to the stability limit of the liquid products in terms of P-value stability index (1.10-1.20).21,22 LHSVs spanned a common range for thermal cracking of 1-3 h-1, except for the low temperature evaluation carried out at 380 ºC where lower space velocities between 0.25-0.75 h-1 were used in order to have conversions within similar levels. Due to the limited availability of virgin DAO, only 6 conditions were evaluated, selecting two LHSVs at three different temperatures: 409, 416 and 423 ºC. All reactions were carried out at a pressure of 300 psig and 5 %wt. steam. Due to the need to heat up the DAO feedstock to be able to mobilize it, LHSV was defined at pumping conditions for all experiments as expressed in Eq. 1. LHSV ℎ =

140 ° !" 300 $%& /ℎ

(

Eq. 1

Additionally, looking forward to evaluating the influence of pressure on the recycled DAO thermal cracking, a set of 6 experiments was carried out varying the total operating pressure and the steam partial pressure. The first 3 experiments were run at a constant pressure of 300 psig and changing the steam content from 2.5, 5.0 and 7.5 %, and compensating with nitrogen in order to keep similar gas levels in the reactor as those produced under the maximum steam


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content of 7.5 % wt., assuming that hydrocarbon gases generated by changing steam/nitrogen content are not significant. In this way, the liquid hold-up is the same for the three conditions and any difference on product quality or reactivity can be attributed to the effect of the partial pressure of steam in the reactor. The last three experiments were performed using a total pressure of 150, 225, and 300 psig with constant 5% wt. steam. In order to compare the reactivity at each condition, the conversion of the hydrocarbons that boil at temperatures above 560 ºC (HC 560°C+) was used as defined in Eq. 2: Conversion =

% 2 3560 °C +7 899: − % 2 3560 °C +7 :?@A ∗ 100% % 2 3560 °C +7 899:

Eq. 2

2.3. Feedstock and product characterization In order to assess and compare the performance of the reactivity tests in terms of quality of the products and to provide the information required for kinetic modeling, liquid and gas product samples were collected and analyzed. Simulated distillation is performed to determine weight percentage of each lump following the ASTM D7169-05 method in an Agilent 6890N chromatograph equipped with automatic injection as described in detail by Carbognani et al.23 In order to determine the state of peptization of the asphaltenes in the liquid product samples, the Pvalue method described by Di Carlo and Janis22 was used. This method consists of the determination of the maximum dilution of the sample with hexadecane at which asphaltenes are not precipitated when observed in an optical microscope with a magnification of 40X. The Pvalue is calculated following Eq. 3. P − value = 1 +

2G"!

1 & %$

Eq. 3


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Microcarbon Residue (MCR) was determined following the muffle furnace method developed by Hassan et al.24 This analysis provides an indirect measurement of the capability of the samples to produce coke and also gives useful information about the extent of advance of the undesired condensation reactions taking place during thermal cracking of residual hydrocarbons. The API gravity of the liquid products was calculated as defined in the ASTM D287-92 standard method, for which it was necessary to determine the specific gravity of the sample. For this, a digital densitometer Rudolph Research Analytical model DDM2911 was used as described with more detail by Carbognani et al.25 Two dilutions in toluene at concentrations close to 0.5 % v/v and 1 %v/v were prepared and their densities were measured in the equipment. Then, the density of the pure sample was extrapolated by assuming an ideal mixture for diluted solutions of components with similar polarity and assuming additive volumes following Eq. 4. HIJKLM9 =

IJKLM9

N1PHA>M?9O9 QNIJKLM9 + A>M?9O9 Q − 31/HA>M?9O9 7A>M?9O9

Eq. 4

Where IJKLM9 is the mass of the sample, HIJKLM9 is the density of the sample, HA>M?9O9 is the

density of toluene used for dilution and A>M?9O9 is the mass of toluene added. The viscosity was measured in a Brookfield viscometer model DV-II+ coupled with a water recirculation system

model TC-502 that allows measurements between 0 and 100 °C. Hydrocarbon group-type separation analysis of Saturates, Aromatics, Resins and Asphaltenes (SARA) was also carried out for all liquid samples, not only to quantify the amount of asphaltenes generated by thermal cracking required for kinetic modeling, but to acquire important information about the reactivity of different hydrocarbon groups when submitted to thermal cracking.

This analysis was

performed following the procedure developed by Carbognani et al.26 Gas samples were analyzed inline using an SRI Instruments chromatograph model 8610C equipped with 4 packed columns, two switching valves, 2 thermal conductivity detectors (TCD), one operating with Argon as


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carrier gas to detect hydrogen at low concentrations and the other with Helium as carrier gas to determine hydrogen at high concentrations and the remaining permanent gases and light hydrocarbons. A Flame Photometric Detector (FPD) provided sulfur compounds analysis (mainly H2S) and a Flame Ionization Detector (FID) was used for analysis of light hydrocarbons. 2.4. Kinetic Modeling For modeling of the experimental data, a plug-flow reactor (PFR) model was assumed. In this case, an isothermal reaction with negligible radial variations at steady state was considered. The mathematical expression to represent the PFR model is given by: "RS "RS = = WS "T "31/U2V 77

Eq. 5

Where RS is the weight fraction of lump i, T is the space time, and WS is the reaction rate for lump i. A first order rate law has shown good results not only for modeling hydrocracking reactions using the lumping technique, but more importantly for catalytic steam cracking and thermal cracking reactions under similar conditions as those proposed in this work.18 In this way, the first

order rate law expressed in Eq. 6, where XS is the kinetic constant for reaction i, was adopted for each reaction.

WS = XS ∗ RS

Eq. 6

Combining Eq. 5 and Eq. 6 and expressing the global reaction rate for each lump in terms of the specific reaction rates following the kinetic scheme shown in Figure 3, 8 different mass balance equations conforming a system of ordinary differential equations (ODE) was obtained as represented by Eq. 7 to Eq. 14. It was assumed that production of Asphaltenes (Asp-C5) comes directly from the hydrocarbons that boil above 560 °C that are not asphaltenes, namely DAO


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(560 °C+). The recombination of these two lumps represent the Vacuum Residue or VR (560 °C+). "RYILZ[ = X R\Y] 3[^_ °à7 "31/U2V 7

Eq. 7

"R\Y] 3[^_ °à7 = − 3X + Xb + Xc + Xd + X[ + X^ + Xe 7R\Y] 3[^_ °à7 "31/U2V 7

Eq. 8

"Rfgh] = Xb R\Y] 3[^_ °à7 − 3Xi + Xj + X _ + X + X b 7Rfgh] "31/U2V 7

Eq. 9

"Rkgh] = Xc R\Y] 3[^_ °à7 + Xi Rfgh] − 3X c + X d + X [ + X ^ 7Rkgh] "31/U2V 7 "R\S9I9M = Xd R\Y] 3[^_ °à7 + Xj Rfgh] + X c Rkgh] "31/U2V 7

"Rl9=>I9O9 = X[ R\Y] 3[^_ °à7 + X _ Rfgh] + X d Rkgh] "31/U2V 7

Eq. 10

Eq. 11

Eq. 12

"RmJLnAnJ = X^ R\Y] 3[^_ °à7 + +X Rfgh] + X [ Rkgh] "31/U2V 7

Eq. 13

"RhJI9I = Xe R\Y] 3[^_ °à7 + X b Rfgh] + X ^ Rkgh] "31/U2V 7

Eq. 14


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This system of ODEs was numerically integrated within the experimental range of space times using the Runge-Kutta method implemented in a Matlab code. The modeling objective is to find the set of unknown kinetic constants at which the modeled product distribution results as close as possible to the experimental values. An objective function based on the sum of squared errors (SSE) between experimental and modeled compositions defined by Eq. 15 was used to quantify the fitting between experimental and modeled data, as follows: Ot Or

VVo = p pNRS9qL −RSK>: Q us Ss

b

Eq. 15

!v is the number of evaluated temperatures and !L represents the number of experimental points evaluated at each temperature. As suggested by Fathi and Pereira-Almao18, three criteria were considered to find the set of kinetic constants that represent the experimental behavior of the process. The first one is the minimization of the objective function, for which an optimization program was implemented in the Matlab code using the nonlinear optimization algorithm fmincon. This allows for the incorporation of linear constraints during the minimization. The second criterion is that the global experimental reaction rate of transforming the DAO (560 ºC+) to the other 7 lumps has to be as close as possible to the sum of the specific reaction rates of DAO (560 ºC+) to each lump

(XwM>xJM yz{ 3[^_ ºà7 = X + Xb + Xc + Xd + X[ + X^ + Xe ), with XwM>xJM yz{ 3[^_ ºà7 calculated

from the experimental values by estimating the slope of the plot 31/U2V 7S vs.

!3R_ ⁄RA 7\Y] 3[^_ °à7 , where R_ is the concentration of DAO (560 °C+) in the feedstock and RA

is the concentration of DAO (560 °C+) in the whole liquid products at each evaluated space time. Finally, the last criterion considered was that the reaction rate constants should follow the Arrhenius law expressed by Eq. 16 :


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ln3XS 7 = ln3S 7 −

oS (~

Eq. 16

When estimating kinetic parameters, the values of the reaction rate constants can be

obtained at each temperature and then Eq. 16 is used to estimate the activation energy (oS 7 and the pre-exponential factor 3S 7 by using linear regression, or the minimization algorithm can be expressed as a function of the activation energy and the pre-exponential factor for each reaction and the whole set of experimental points is optimized in one step. The advantage of the first case is that the number of parameters to be optimized at each temperature is lower, but there is the disadvantage of having higher chances of fitting errors in the linear regression of the Arrhenius

equation that would represent higher global error for the kinetic model due to its exponential nature. On the other hand, in the second scenario it is guaranteed that the kinetic parameters follow the Arrhenius equation, but the optimization is much more difficult due to the higher number of parameters and also the high non-linearities introduced in the system of ODEs with the exponential form of the Arrhenius expression, causing the ODE solver not to converge to a solution, which can be overcome by having an analytical solution for the system of ODEs usually very complex for such a high number of reaction paths. To avoid this, a different approach was considered in this work, with similarities to the one proposed by Da Silva.16 The Arrhenius equation was not directly replaced in the system of ODEs, but its dependence was included by means of modification in the objective function that accounts for the error in the

linear regression of Eq. 16 as represented in Eq. 17, where != is the number of reactions in the kinetic scheme, and is the coefficient of determination for the linear fitting of the Arrhenius equation of each reaction. In this way, the whole set of data was optimized in a single step. A similar approach was also implemented by Taghipour and Naderifar8 for kinetic modeling of vacuum residue thermal cracking.


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Ot Or

VVo = p pNRS us Ss

9qL

b

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O

b

−RSK>: Q + != − p s

Eq. 17

The Average Absolute Error (AAE) between the experimental and model results for each lump was also calculated in the Matlab code following Eq. 18, where k represents each lump (1 to 8) o % =

r t ∑Ous ∑Ss

O

9qL K>: R,S −R,S 9qL R,S

!v + !L

∗ 100

Eq. 18

These types of kinetic modeling have the characteristic of having multiple solutions. Therefore, different patterns can be obtained for the kinetic constants, activation energies and pre-exponential factors depending on the initial seed for the multivariable optimization, the algorithm used, the number of reactions involved, etc. For this reason, it is of paramount importance to incorporate chemical considerations into the mathematical modeling in such a way that the obtained results are in agreement with what is expected for a thermal cracking reaction of a residual hydrocarbon. To address these aspects, three scenarios were evaluated following the analysis of lumped kinetic model for hydrocracking of heavy residue developed by Asaee et al.27: •

Case 1 (No sequence): kinetic parameters were obtained without any chemical constraint using the mathematical modeling described in this section.

•

Case 2 (Sequence 1): Activation energies of thermal cracking of heavier lumps are lower than lighter ones since larger molecules require less energy to be cracked. Furthermore, a sequence was imposed on the activation energies in such a way that the activation energy of conversion of a lump to lighter products is lower than to heavier products. In addition,


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constraints on the kinetic constant of gas production were imposed in such a way that gas

production proceeds more readily from heavier lumps (Xe > X b > X c ). •

Case 3 (Sequence 2): Activation energies of thermal cracking of heavier lumps are lower than lighter ones. Furthermore, a sequence was imposed on the activation energies in such a way that the activation energy of conversion of a lump to lighter products is higher than to heavier products. Similar constraints as in Case 2 were placed on the kinetic constants for gas production.

Looking forward to evaluating if there was any difference in the calculated kinetic parameters when comparing the proposed 8-lumps model presented in Figure 3, a simplified 6lumps model as shown in Figure 4 was used. The same mathematical approach described in this section was followed. The number of kinetic constants to be determined at each temperature using the simplified 6-lumps model is 8 instead of the 16 required to represent the reactions in the 8-lumps model. The comparison was conducted only for recycled DAO thermal cracking without using any constraint in the optimization algorithm (case 1- no sequence). Finally, in order to quantify the experimental error of the measured weight fractions for each one of the kinetic modeling lumps due variability for different mass balances in the pilot plant run as well as the variability in the characterization techniques (SimDist and nC5-asphaltenes by micro-deasphalting), two different experiments from the pilot plant commissioning reported were analyzed. In each one of those experimental runs conducted at different severity levels, three mass balances were collected and analyzed. An average of the relative variance was calculated for each lump.


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3. RESULTS AND DISCUSSION 3.1. Effect of partial and total steam pressure As observed in the experimental data presented in Table 2, no significant effect on the DAO reactivity was evidenced when changing the steam partial pressure keeping a constant liquid hold up (Pw1, Pw2 and Pw3) in the reactor with values around 40%, which was somehow expected since the effect of steam pressure would be predominant on the enhancement of the product quality by reducing the effect of condensation reactions and coke formation, but not on the reactivity. However, for the levels of steam evaluated in this work slight improvement on the product quality was observed when increasing the content of steam in the reaction media, which suggests that the lower value of 2.5 %wt. already provides a reasonable amount of water for the reaction. On the other hand, when keeping a constant flow of water changing the total operating pressure (Pt1, Pt2 and Pt3), it was possible to observe a slight increase of conversion at the maximum pressure of 300 psig (Pt3), possibly caused by the increase on the liquid hold up and consequently on the effective liquid hydrocarbon residence time in the reactor, giving it more time to react compared to the lower pressure cases (Pt1 and Pt2). In this case (Pt3), a slight increase was also observed on the indicators of the product quality, such as slight reduction on the microcarbon and asphaltenes content and increase on the P-value. However, these enhancements are within the ranges of error of the given characterization techniques, thus it is not possible to affirm that there is a significant improvement. For this reason, it was not attempted to incorporate pressure as a variable for the kinetic modeling of the process. 3.2. Reactivity Analysis In Table 3, a brief summary of the experimental conditions, including mass balances and conversion levels is presented. A range of around 26% of conversion points was explored for the


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recycled DAO runs spanning from a 17.1% of conversion of the 560 °C+ hydrocarbon fraction up to 43.3 %. For the virgin material, a narrower range between 32.7 to 48.2 % was investigated due to higher reactivity and feedstock available.

Additionally, a very good closure of

hydrocarbon mass balances was obtained for the experimental set with an average value of 99.1 % and standard deviation of 1.1 %, which proves the stable operation and reliability of the experimental setup used for this work and strengthen the robustness of the experimental data used for mathematical modeling. Experimental product distributions were normalized to 100 % for data analysis and kinetic modeling. Comparing Exp. No. 4, No. 8 and No. 12 for the recycled DAO feedstock, which are all at the same space velocity of 2 h-1, an increase of 7.5 conversion points was observed by increasing 1.7% the reaction temperature from 409 °C to 416 °C, and an increase of 13.8 when the temperature increased by 3.4% from 409 °C to 423 °C. Conversely, comparing for example Exp. No. 4 and No. 6 both at the same temperature of 409 °C for the same feedstock, an increase of only 9.5 conversion points is observed when decreasing the space velocity and thus the liquid residence time in the reactor by 25% from 2 h-1 to 1.5 h-1. In this way, it is possible to observe how sensible the DAO reactivity is to changes in the reaction temperature compared to the other main variable available to control the reaction severity, i.e., the space velocity. A similar behavior was observed for the virgin feedstock. However, when comparing the reactivity of both feedstocks at similar operation conditions we can see that the 560 °C+ fraction of the virgin material is much more reactive that that of the recycled one, leading to an increase of around 5 conversion points that increase the amount of valuable light products obtained from this heavy fraction. The loss of reactivity for the recycled material is attributed to the consecutive cracking of the non-asphaltene containing hydrocarbon fraction in the upgrading scheme illustrated in Figure 1.


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Reasonable trends were observed for the product distributions as a function of conversion, which are directly related to the severity of the reaction, as can be seen in Figure 5. The amount of heavy cut DAO (560 ºC+) tend to sharply decrease as the conversion increases, while other less heavy cuts in the gasoil range (HVGO and LVGO) remain practically unchanged, possibly because their rate of consumption is similar to their rate of generation under the thermal reactions taking place. On the other hand, light cuts such as Naphtha, Kerosene and Diesel moderately increase. This is a typical behavior of a visbreaking process.2,28 Now considering the undesirable products, gas yields between 3.8 to 6.2 % wt. and 2.8 to 4.7 % wt. were obtained for the range of conversions evaluated, while the pentane insoluble asphaltenes in the thermal cracking products were between 7.1 and 13.3 % wt and 4.6 to 10.1 % wt for recycled and virgin DAO respectively, for the minimum and the maximum conversions. Analyzing now the stability of the liquid products represented by the P-value index shown in Figure 5 as a function of conversion, it is possible to see a considerable deterioration of the stability of the asphaltenes molecules produced during thermal processing, reaching the commonly accepted instability value of 1.15-1.20 that suggests asphaltenes precipitation that may lead to equipment fouling in industrial operations at the conversion level of 43 % for both feedstocks. Operation beyond this conversion level, besides promoting instabilities in the liquid product, would trigger the production of insoluble materials, mainly coke, and would also increase the yield of gas, consequently reducing the effective liquid yield of more valuable products in the overall process, which would not be economically convenient. As illustrated in Figure 6, the ln(viscosity) measured at 25 ºC follows a linear trend of the conversion with a correlation factor of 0.9922 for the recycled DAO and 0.9955 for the virgin one. As expected for a visbreaking process, the viscosity of the liquid product is reduced by


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several orders of magnitude at the maximum conversions for both cases. It is important to highlight the parallelism on the viscosity reduction trends for both feedstocks, which suggests that the extent of viscosity reduction is mainly controlled by the degree of conversion achieved and is not appreciably influenced by the difference in chemical nature of both materials in terms of the higher amount of partially cracked molecules present in the recycled DAO compared to the virgin one. However, the viscosity values for virgin DAO and its products are higher than for recycled VGO, which could also be explained by the higher branching of the molecules in the virgin and its products from thermal cracking, than for the recycled DAO and its thermal cracking products, which are less branched and more aromatic. Conversely, API gravity slightly increased 2 points and 4 points at the maximum conversions achieved for both recycled and virgin DAO respectively, which suggests that there is in fact a density increase attainable at similar operational conditions due to the recycling effect in the upgrading loop. A similar behavior was observed for the amount of microcarbon residue obtained for both cases, as discussed in the ensuing text. As observed in Figure 7, recycled DAO has a higher tendency to form insoluble materials (MCR) when compared to the virgin one at similar conversion due to the fact that even though cracked molecules can be within the same boiling point range as virgin ones, their chemical composition is different with the possible presence of high aromaticity compounds that are more prone to condensation reactions leading to coke formation. Considering now the stability of the asphaltenes present on the thermally cracked products, it was expected to obtain a more stable product with a higher P-value at the same conversion levels for the virgin material, but on the experimental results presented in Figure 7 it was observed that the P-value trend was conversion driven, with both lines practically overlapping. One possible explanation for this phenomenon is


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that the deterioration of the asphaltenes stability due to thermal cracking leading to their precipitation at higher conversions is mainly controlled by the nature of the first asphaltenes that are generated from thermal cracking of the virgin material and once they are removed by solvent deasphalting and the DAO is submitted again to thermal cracking, the asphaltenes generated in those subsequent steps systematically decrease their stability, presumably because their bulk nature is similar as a function of conversion severity. 3.3. Kinetic study A good fitting between the experimental and model data was obtained for recycled DAO and virgin DAO thermal cracking kinetic model without any sequence or constraint on the activation energies. The linear regression of the plot of compositions obtained by the model vs. the experimental compositions has a coefficient of correlation close to 1 for both recycled and virgin feedstock as shown in Figure 8 and Figure 9 respectively. A similar behavior was obtained for the other two evaluated scenarios (Case 2 and 3) for both feedstocks. Taking a look at the modeling error for each lump illustrated in Figure 10, no significant variation was obtained on the global average absolute error for Case1 (recycled DAO 6.72 % and virgin DAO 7.01 %), Case 2 (recycled DAO 7.00 % and virgin DAO 6.62 %) and Case 3 (recycled DAO 7.02 % and virgin DAO 7.03 %). Thus, the implementation of chemical considerations within the mathematical modeling did not have an effect on the accuracy and the capability of the model to represent the experimental data and the modeling error cannot be used as a decisive factor to choose which scenario best represents the chemistry involved in the thermal cracking of these feedstocks. It was observed that overall the lighter the lump the higher the error, except for the residual hydrocarbons with boiling points above 560ºC+ that in this case are the DAO (560ºC+) and the Asp-C5 lumps. This is possibly related to the accuracy of the simulated distillation


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method used for determining boiling point distribution of feed and products that is known to have a higher error for the residual hydrocarbons compared to other lumps.23 Additionally, the determination of pentane insoluble asphaltenes has a high relative error as in ASTM D893 and D2007 methods. It is important to highlight that, besides the modeling error, there is an experimental error associated to each pilot plant experiment. Table 4 presents an analysis of the variability of the lump composition determination based on two experimental runs at different operating conditions performed during the pilot plant commissioning. Three mass balances were analyzed for each run and the average composition, standard deviation, and relative variance were reported. Figure 11 presents the average lump composition for both experimental tests with the error bars calculated using the average relative variance reported in Table 4. As can be observed, the variability in terms of weight fraction is considerably higher for the residual lumps DAO (560 °C+) and the Asp-C5. In addition, the naphtha cut presents a significant variability. On the other hand, the weight fraction variability of intermediate lumps (kerosene, diesel, LVGO and HVGO) is lower than DAO (560 C+), Asp-C5 and naphtha. The lowest variability was obtained for the gases lump. The global activation energy for the conversion of DAO (560ºC+) to other lumps is 241 [kJ/mol] and 226 [kJ/mol] for recycled DAO and virgin DAO regardless of the evaluated case, which both fall within the common range for thermal cracking reactions, as well as the activation energies of conversion of other lumps.9 The most important finding of the type of modeling adopted in this work (including an asphaltenes production route), is getting to know how fast and how likely it is to produce an undesired amount of asphaltenes compared to the conversion


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reactions of DAO (560 ºC+) to lower boiling point range hydrocarbons that are economically valuable. As presented in Table 5 and Table 6 for recycled and virgin DAO kinetic modeling respectively, this reaction is in the same order of magnitude as the conversion reactions, which definitely is a limitation of the thermal cracking process since considerable amounts of nonvirgin asphaltenes are being produced to a similar extent as that of valuable products. Careful selection of process operation conditions (temperature, residence time) has to be done in such a way that this reaction step leading to asphaltenes generation is inhibited keeping the produced asphaltenes content as low as possible while the others pathways leading to liquid products are favored, producing in this way a higher amount of desirable products preferably within the gas oil and distillates range. It is very important to indicate how the chemical composition of the feedstock can impact the velocity of generation of asphaltenes. For the different evaluated scenarios for recycled and virgin DAO kinetic modeling, it can be observed that the ratio of kinetic constants for asphaltenes production (X 7 from recycled DAO (560 ºC+) and virgin DAO (560 ºC+) is around 2. This indicates that even though both feedstocks lack asphaltenes and come from similar reservoirs they have different chemical characteristics that lead to considerably higher production of asphaltenes from the recycled material compared to the virgin one. This could be explained considering how each feedstock is produced following the upgrading scheme shown in Figure 1. Virgin DAO comes from direct solvent deasphalting of Vacuum Residue (560ºC+) using pentane, but without having the thermal cracking recycling loop.

On the other hand, for the recycled DAO, deasphalted oil is kept on a thermal

cracking/separation loop in such a way that only the lighter hydrocarbons are produced (Gas, Naphtha, Kerosene, Diesel, LVGO and HVGO), the asphaltenes are rejected along with some resins for gasification and the DAO (560ºC+) is kept in the thermal cracking loop having always


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some proportion of fresh bitumen coming in. In this way, recycled DAO (560ºC+) would be composed of a portion of virgin or unprocessed hydrocarbons and a majority of material that has been cracked or partially converted several times. In this order of ideas, the reactivity of this recycled DAO (560ºC+) lump would come from cracking of heavy aromatic and polyaromatic hydrocarbons since dealkylation and removal of easy-to-crack hydrocarbons has been occurring for several cycles. Thermal cracking of these heavy compounds promotes faster polymerization and condensation reactions to form asphaltenes that are precursors to form insoluble materials such as coke, compared to a virgin DAO feedstock which still possesses alkyl moieties able to react initially. Taking a look at the kinetic parameters presented in Table 5 and Table 6, the following remarks can be advanced: Case 1 (No sequence): a decreasing trend can be observed when comparing the activation energies of conversion of DAO (560ºC+) to heavier compounds compared to lighter ones for recycled DAO, while the opposite behavior was observed for virgin DAO. No clear pattern was observed for the conversion of the HVGO lump for both feedstocks, whereas LVGO showed lower activation energies towards the production of heavier lumps for recycled DAO and the opposite behavior was found for virgin DAO. Additionally, activation energies of conversion of heavier lumps are lower compared to lighter ones for recycled DAO with the following values: 241, 278 and 269 [kJ/mol] for DAO (560ºC+), HVGO and LVGO respectively. On the contrary, for virgin DAO activation energies of conversion of heavier lumps are higher compared to lighter ones for virgin DAO, these are: 226, 214 and 188 for DAO (560ºC+), HVGO and LVGO respectively. In Case 1, no constraints were placed on the mathematical model for the reactions leading to gas production and, as can be observed on the kinetics constants at 423 ºC, the heavier


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the hydrocarbon the lower its kinetic constant for gas production (Xe < X b < X c ) for both feedstocks. Case 2 (Sequence 1): activation energies of conversion of heavier lumps are lower compared to lighter ones for both feedstocks. The following values were obtained: 241, 277 and 300 for DAO (560ºC+), HVGO and LVGO respectively for recycled DAO and 226, 246 and 280 [kJ/mol] for virgin DAO. Therefore, the constraints imposed on the mathematical modeling to obtain higher activation energies for conversion of lighter lumps were satisfied in both cases. Likewise, the sequences implemented for conversion of each lump were satisfied since for each of the reacting lumps the activation energies have a decreasing trend to lighter lumps compared to heavier ones. Moreover, the constraints on the kinetic constants to gas production (Xe , X b & X c) were also satisfied and gas production proceeds more readily from heavier lumps. Analyzing the values of the kinetic constants at 423 ºC, it can be observed that for recycled DAO, DAO (560ºC+) reacts faster towards HVGO, LVGO and the undesired reaction to Asp-C5 compared to any other lumps, so the selectivity towards distillates and naphtha is low. Similarly, these reactions are also predominant for the fraction DAO (560ºC+) of the virgin material. However, in the case of virgin DAO the velocity of production of HVGO and LVGO is higher compared to the reaction to Asp-C5. Also, the generation of naphtha and distillates from virgin and recycled DAO (560ºC+) is at similar levels, while the gas generation is lower for the virgin material. In the same way, HVGO converts more readily to its subsequent lighter lump LVGO compared to any other lump, with kinetic constant to LVGO more than 4 times higher than to diesel, kerosene, naphtha for recycled DAO and twice higher for virgin DAO following the same pattern. Conversely, LVGO thermal cracking has higher selectivity towards kerosene and naphtha as compared to diesel for both evaluated feedstocks.


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Case 3 (Sequence 2): Similar to Case 2, activation energies of conversion of DAO (560ºC+), HVGO and LVGO followed a decreasing trend. The following values were obtained: 241, 243 and 249 [kJ/mol] for DAO (560ºC+), HVGO and LVGO respectively for recycled DAO and 226, 230 and 244 [kJ/mol] for virgin DAO. In the same way, the mathematical algorithm satisfied the constraints imposed. On the other hand, the sequences implemented in the mathematical modeling for conversion of each lump were also satisfied since for DAO (560ºC+), HVGO and LVGO the activation energies have an increasing trend to lighter lumps compared to heavier ones. Similar to Case 2, constraints on the kinetic constants for gas production were satisfied. Overall, selectivities of each lump followed a similar pattern as in Case 2, with some slight variations on the actual values of the kinetic constants. The results obtained in Case 1 show that there is not any pattern that would align with the thermal cracking chemistry if no restrictions are placed during the mathematical modeling. The algorithm would obtain a solution within a reasonable modeling error, but it would not be possible to give a physical explanation to the results, especially for complex systems involving several lumps and reactions as those evaluated in this work. For example, kinetics constants for gas production from lighter compounds are higher than from heavier compounds, which would not be the expected trend for visbreaking of residual hydrocarbons since gas production proceeds more readily from heavy fractions.2,28,29 Additionally, even though it would depend on the type of bonds that are broken in each of the lumps, overall it is expected to have lower activation energies for conversion of heavier lumps due to the increased crackability of higher boiling point range hydrocarbons compared to lower ones. As can be seen for Case 1, this trend was not obtained for the 3 reacting lumps for either of the feedstocks. Therefore, it is necessary to take into consideration the chemical aspects that can be possibly incorporated into the mathematical


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solution of the lumped kinetic model and constrain it in such a way that it fulfills these requirements. This is in agreement with what was found by Asaee et al.27 for hydrocracking of heavy residua. The sequence of activation energies in Case 2 suggests that the production of lighter compounds comes from the thermal cracking of bonds that require less energy to break as compared to the production of heavier lumps. For example, a hydrocarbon with significant content of asphaltenes that are known to have high presence of alkyl chains would have low activation energy towards the production of naphtha and gases compared to hydrocarbons within the HVGO or LVGO range where their production would come from breakage of internal C-C bonds. It is important to highlight that most polyaromatic rings with high content of alkyl chains are commonly present on the asphaltenes fraction that are absent in both feedstocks evaluated in this work. However, asphaltenes generated during thermal cracking would not have the same characteristic since their structural composition would be considerably lower in alkyl moieties compared to a virgin asphaltenes. On the contrary, the sequence in Case 3, where activation energies for production of lighter lumps are higher than those for heavier lumps, would be suitable for example for a feedstock where there is a lower chance of dealkylation reactions taking place. In this case, cracking of hydrocarbon molecules towards production of light lumps would require more energy to occur and therefore would be promoted at higher temperatures. Therefore, Case 3 would be a more appropriate approach for kinetic modeling of DAO. Taking a closer analysis on the DAO (560°C+) lump, which is the lump of most interest, if it is assumed that a recycled and virgin DAO are composed by only this fraction (perfect distillation cut at 560 °C), the initial velocity of formation of each lumps at 423 °C can be calculated using Eq. 6 and compared for each lump relative to the global velocity of reaction for both feedstocks. This allows a simple comparison of the preferential pathways using the modeling results assuming


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both feedstocks had the same lump composition. As illustrated in Figure 12, production of asphaltenes almost doubles and production of HVGO and LVGO is considerably lower when comparing recycled and virgin DAO. This confirms a strong change on selectivities for both deasphalted materials with the same boiling point range due to their differences in chemical nature caused by the sequential cracking of the converted DAO as explained previously. All these aspects are highly dependent on the detailed characterization of the evaluated material at a molecular level, which is very often not feasible for kinetic modeling based on a lumping technique where thousands of different compounds are grouped in a single lump. Nonetheless, this type of models plays an important role for simulation and optimization of industrial process and still bulk chemical characteristics of the feedstock can be implemented in the modelling to obtain a solution that makes physical sense for the process under study as was done in this investigation. As presented in Table 7, where the kinetic parameters for converted DAO thermal cracking using a 6-lumps kinetic model are reported, all the constraints imposed in the optimization algorithm were satisfied. This result is similar to the obtained for the 8-lumps model. In the same way, the values for oS and S are very similar to the obtained for the 8-lumps model. Taking a

look at the kinetic constants at 423 °C for both 8-lumps and 6-lumps models, if the kinetic constants of formation of HVGO and LVGO from DAO (560 °C+) for the 8-lumps model are

grouped (Xb + Xc = 0.4003 + 0.3686 = 0.7689 ℎ 7, the actual value is very close to the

obtained for the production of full-range VGO (343+560) using the 6-lumps model (Xb =

0.7900 ℎ 7. A similar result is obtained if diesel and kerosene are grouped. In this case, the grouped value of the formation of diesel and kerosene from DAO (560 °C+) for the 8-lumps

model (Xd + X[ = 0.1985 + 0.0692 = 0.2377ℎ 7 is in the same order of magnitude to the


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obtained for the production of distillates using the 6-lumps model (Xc = 0.7900 ℎ 7. Formation of gases and asphaltenes from DAO (560 °C+) is also very similar for both models. Based on the previous observations, there is no significant difference in the kinetic parameters obtained when using a robust 8-lumps model, which represents in more detail the transformations of the different fractions present in the DAO feedstock. From an error analysis point of view, a very good fit between the experimental and model data was obtained for the 6lumps model as depicted in Figure 13. The linear regression of the plotted data has a coefficient of correlation close to 1. Comparing the global average absolute errors (GAAE), it is very interesting to see that for the 6-lumps model, the GAAE is higher than the one obtained for the 8-lumps model (8.20 vs. 7.02 %), which could indicate that using 8-lump represents better the thermal cracking reactions taking place. It is important to highlight that, contrary to what could be expected when having a high number of lumps, the quality of the adjustment is better when the definition of the pseudo components is more precise. This gives an indication that the system tolerates a higher number of pseudo components to represent the reactions taking place.

4. CONCLUSIONS Reactivity of a pre-cracked deasphalted vacuum residue (recycled DAO) and a virgin deasphalted vacuum residue (virgin DAO) from Northern Alberta was evaluated spanning a relatively wide range of operating conditions and conversion levels. Experimental conditions were chosen to resemble an industrial thermal cracking operation. This allowed us to create correlations to estimate the properties of the whole liquid product as a function of conversion. Effects of LHSV, temperature and pressure on the performance of the process were found to have a similar behavior as for upgrading of residual hydrocarbons via thermal cracking. The absence of asphaltenes on the feedstock resulted in an enlarged limit stability that allowed the


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process to reach higher conversion levels compared to thermal cracking of asphaltenes containing hydrocarbon fractions such as vacuum residue. Total operating pressure and steam partial pressure had slight effects on the DAO reactivity at the range of operating conditions evaluated. Despite the absence of asphaltenes on the evaluated feedstocks, a considerable yield of these compounds was obtained especially when the pre-cracked feedstock was used, which highlights the importance of this undesirable reaction in the reactions scheme. Very importantly, it was found that significant differences in asphaltenes and gasoil production are obtained for materials with similar boiling point ranges, however having differences in their chemical nature with converted feed expectably more aromatic and less branched than virgin feed. From the kinetic point of view, it was possible to incorporate the reaction of coke precursors (asphaltenes) generation using the lumping technique for vacuum residue DAO thermal cracking with a reasonable modeling error around 7 % and for three different scenarios of sequences on the activation energies and restrictions on kinetic constants to account for chemical considerations. Kinetic parameters were within common values found in the literature. Case 3, which incorporate modifications based on chemical reactivity considerations, was found to be the most appropriate for kinetic modeling of deasphalted oil thermal cracking. Learnings applied being activation energies for the conversion of heavier lumps are lower than those for conversion of lighter ones and the activation energies of formation of lighter lumps are higher than those for the formation of heavier lumps. No relevant differences were observed between the kinetic parameters obtained for the 8-lumps model compared to the 6-lumps approach for DAO thermal cracking. This indicates that in this particular case, the quality of the adjustment is better when the definition of the pseudo components is more precise, having a higher number of lumps to model the thermal cracking reactions taking place.


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ACKNOWLEDGEMENT The authors are grateful to the Natural Sciences and Engineering Research Council of Canada (NSERC), Nexen-CNOOC Ltd, and Alberta Innovates-Energy and Environment Solutions

(AIEES)

for

the

for

the

financial

support

provided

through

the NSERC/NEXEN/AIEES Industrial Research Chair in Catalysis for Bitumen Upgrading. Also, the contribution of facilities from the Canada Foundation for Innovation, the Institute for Sustainable Energy, Environment and Economy, the Schulich School of Engineering and the Faculty of Science at the University of Calgary are greatly appreciated. Finally, the technical contributions and guidelines provided by Nestor Zerpa, Senior Engineering Advisor at Nexen Energy ULC, for the development of this investigation are greatly appreciated.

REFERENCES (1) Ancheyta, J.; Trejo, F.; Rana, M. S., Asphaltenes: Chemical Transformation During Hydroprocessing of Heavy Oils. Taylor & Francis Group: 2009. (2) Speight, J. G. Visbreaking: A technology of the past and the future. Scientia Iranica 2012, 19 (3), 569-573. (3) Speight, J. G., Chapter 2 - Thermal Cracking. In Heavy and Extra-heavy Oil Upgrading Technologies, Gulf Professional Publishing: Boston, 2013; pp 15-38. (4) Puron, H.; Arcelus-Arrillaga, P.; Chin, K. K.; Pinilla, J. L.; Fidalgo, B.; Millan, M. Kinetic analysis of vacuum residue hydrocracking in early reaction stages. Fuel 2014, 117, Part A (0), 408-414.


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(5) Sánchez, S.; Rodríguez, M. A.; Ancheyta, J. Kinetic Model for Moderate Hydrocracking of Heavy Oils. Ind. Eng. Chem. Res. 2005, 44 (25), 9409-9413. (6) Ancheyta, J.; Sánchez, S.; Rodríguez, M. A. Kinetic modeling of hydrocracking of heavy oil fractions: A review. Catal. Today 2005, 109 (1–4), 76-92. (7) Souza, B. M.; Travalloni, L.; da Silva, M. A. P. Kinetic Modeling of the Thermal Cracking of a Brazilian Vacuum Residue. Energy Fuels 2015, 29 (5), 3024-3031. (8) Taghipour, A.; Naderifar, A. Kinetic Modeling of Vacuum Residue Thermal Cracking in the Visbreaking Process Using Multiobjective Optimization. Energy Technology 2015, 3 (7), 758767. (9) Singh, J.; Kumar, S.; Garg, M. O. Kinetic modelling of thermal cracking of petroleum residues: A critique. Fuel Process. Technol. 2012, 94 (1), 131-144. (10) Kataria, K. L.; Kulkarni, R. P.; Pandit, A. B.; Joshi, J. B.; Kumar, M. Kinetic Studies of Low Severity Visbreaking. Ind. Eng. Chem. Res. 2004, 43 (6), 1373-1387. (11) Kerr, R.; Birdgeneau, J.; Batt, B.; Yang, P.; Nieuwenburg, G.; Rettger, P.; Arnold, J.; Bronicki, Y., The Long Lake Project - The First Field Integration of SAGD and Upgrading. In SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference Calgary, Alberta, Canada, 2002. (12) Del Bianco, A.; Panariti, N.; Anelli, M.; Beltrame, P. L.; Carniti, P. Thermal cracking of petroleum residues. Fuel 1993, 72 (1), 75-80. (13) Singh, J.; Kumar, M. M.; Saxena, A. K.; Kumar, S. Reaction pathways and product yields in mild thermal cracking of vacuum residues: A multi-lump kinetic model. Chem. Eng. J. 2005, 108 (3), 239-248.


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(14) Mohaddecy, S. R. S.; Sadighi, S. Simulation and Kinetic Modeling of Vacuum Residue Soaker-Visbreaking. Petroleum and Coal 2011, 53 (1), 26-34. (15) Loria, H.; Trujillo-Ferrer, G.; Sosa-Stull, C.; Pereira-Almao, P. Kinetic Modeling of Bitumen Hydroprocessing at In-Reservoir Conditions Employing Ultradispersed Catalysts. Energy Fuels 2011, 25 (4), 1364-1372. (16) Da Silva De Andrade, F. Kinetic modeling of catalytic in situ upgrading for Athabasca bitumen, deasphalting pitch and vacuum residue. MSc Thesis, University of Calgary, Calgary, 2014. (17) Galarraga, C. E.; Scott, C.; Loria, H.; Pereira-Almao, P. Kinetic Models for Upgrading Athabasca Bitumen Using Unsupported NiWMo Catalysts at Low Severity Conditions. Ind. Eng. Chem. Res. 2011, 51 (1), 140-146. (18) Fathi, M. M.; Pereira-Almao, P. Kinetic Modeling of Arab Light Vacuum Residue Upgrading by Aquaprocessing at High Space Velocities. Ind. Eng. Chem. Res. 2012, 52 (2), 612623. (19) Fathi, M. M. Comparative Upgrading of Arab Light Vacuum Residuum via Aquaprocessing and Thermal Cracking. PhD Thesis, University of Calgary, Calgary, 2011. (20) Trujillo-Ferrer, G. Thermal and Catalytic Steam Reactivity Evaluation of Athabasca Vacuum Gasoil. MSc Thesis, University of Calgary, Calgary, 2008. (21) Fathi, M. M.; Pereira-Almao, P. Catalytic Aquaprocessing of Arab Light Vacuum Residue via Short Space Times. Energy Fuels 2011, 25 (11), 4867-4877. (22) Di Carlo, S.; Janis, B. Composition and visbreakability of petroleum residues. Chem. Eng. Sci. 1992, 47 (9), 2695-2700.


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Energy & Fuels

(23) Carbognani, L.; Lubkowitz, J.; Gonzalez, M. F.; Pereira-Almao, P. High Temperature Simulated Distillation of Athabasca Vacuum Residue Fractions. Bimodal Distributions and Evidence for Secondary “On-Column” Cracking of Heavy Hydrocarbons. Energy Fuels 2007, 21 (5), 2831-2839. (24) Hassan, A.; Carbognani, L.; Pereira-Almao, P. Development of an alternative setup for the estimation of microcarbon residue for heavy oil and fractions: Effects derived from air presence. Fuel 2008, 87 (17–18), 3631-3639. (25) Carbognani Ortega, L.; Rogel, E.; Vien, J.; Ovalles, C.; Guzman, H.; Lopez-Linares, F.; Pereira-Almao, P. Effect of Precipitating Conditions on Asphaltene Properties and Aggregation. Energy Fuels 2015, 29 (6), 3664-3674. (26) Carbognani, L.; Gonzalez, M. F.; Pereira-Almao, P. Characterization of Athabasca Vacuum Residue and Its Visbroken Products. Stability and Fast Hydrocarbon Group-Type Distributions. Energy Fuels 2007, 21 (3), 1631-1639. (27) Asaee, S. D. S.; Vafajoo, L.; Khorasheh, F. A new approach to estimate parameters of a lumped kinetic model for hydroconversion of heavy residue. Fuel 2014, 134, 343-353. (28) Speight, J. G.; Ozum, B., Petroleum Refining Processes. Taylor & Francis: 2001. (29) Gray., M. R., Upgrading oilsands bitumen and heavy oil. The University of Alberta Press: Edmonton, 2015.


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Page 34 of 51

List of Figures Figure 1. SDA/TC-based upgrading scheme Figure 2. Schematic of the experimental setup for reactivity tests Figure 3. Proposed kinetic model for DAO thermal cracking Figure 4. 6-lumps kinetic model for DAO thermal cracking. Figure 5. Product distributions and P-value vs. VR (560 °C+) conversion for recycled and virgin DAO thermal cracking Figure 6. Viscosity and API gravity vs. vacuum residue (560 °C+) conversion Figure 7. MCR residue and P-value profiles vs. vacuum residue (560 °C+) conversion Figure 8. Predicted model composition vs. experimental composition for Case 1(unconstrained) recycled DAO kinetic model. Figure 9. Predicted model composition vs. experimental composition for Case 1(unconstrained) virgin DAO kinetic model. Figure 10. Comparison between the modeling error by lump for recycled and virgin DAO kinetic modeling Figure 11. Average lump composition with error bars Figure 12. Initial velocities of formation of each lump at 423 °C for DAO (560 °C+). Figure 13. Predicted model compositions vs. experimental compositions for case 3 - converted DAO for a 6-lumps kinetic model.


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Energy & Fuels

Figure 1. SDA/TC-based upgrading scheme


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Energy & Fuels

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Figure 2. Schematic of the experimental setup for reactivity tests

Figure 3. Proposed kinetic model for DAO thermal cracking


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Energy & Fuels

Figure 4. 6-lumps kinetic model for DAO thermal cracking.


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Energy & Fuels

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Figure 5. Product distributions and P-value vs. VR (560 °C+) conversion for recycled and virgin DAO thermal cracking


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Energy & Fuels

Figure 6. Viscosity and API gravity vs. vacuum residue (560 °C+) conversion

Figure 7. MCR residue and P-value profiles vs. vacuum residue (560 °C+) conversion


39

Energy & Fuels

0.6

Model Composition [weight fraction]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 40 of 51

Recycled DAO

0.5 y = 1.0573x - 0.0072 R² = 0.9955

0.4

DAO (560 °C+) Asp-C5 HVGO

0.3 LVGO Diesel

0.2

Kerosene Naphtha

0.1

Gas 0.0 0.0

0.1 0.2 0.3 0.4 0.5 Experimental Composition [weight fraction]

0.6

Figure 8. Predicted model composition vs. experimental composition for Case 1(unconstrained) recycled DAO kinetic model.


40

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0.6

Model Composition [weight fraction]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

Virgin DAO

0.5

y = 1.0397x - 0.0049 R² = 0.9976

0.4

DAO (560 °C+) Asp-C5 HVGO

0.3

LVGO Diesel

0.2

Kerosene Naphtha

0.1

Gas 0.0 0.0


0.6

Figure 9. Predicted model composition vs. experimental composition for Case 1(unconstrained) virgin DAO kinetic model.


41

Energy & Fuels

AAE [%]

Recycled DAO

Virgin DAO

20 18 16 14 12 10 8 6 4 2 0

No sequence

Sequence 1

Sequence 2

Figure 10. Comparison between the modeling error by lump for recycled and virgin DAO kinetic modeling

Experimental Compotiion [% wt.]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 42 of 51

40 35 30 25 20 15 10 5 0

Figure 11. Average lump composition with error bars


42

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0.6 Reaction rate [% wt./h]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.5 0.4 0.3

Recycled DAO

0.2

Virgin DAO

0.1 0.0

Figure 12. Initial velocities of formation of each lump at 423 °C for DAO (560 °C+).


43

Energy & Fuels

0.6 Model Composition [weight fraction]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 44 of 51

Recycled DAO - 6 Lumps

0.5

y = 1.0503x - 0.0084 R² = 0.9943

0.4

DAO (560 °C+) Asp-C5

0.3

VGO Distillates

0.2

Naphtha Gases

0.1 0.0 0.0


0.6

Figure 13. Predicted model compositions vs. experimental compositions for case 3 - converted DAO for a 6-lumps kinetic model.


44

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Energy & Fuels

List of Tables Table 1. Feedstocks characterization Table 2. Effect of pressure on recycled DAO thermal cracking. Results reported for the whole liquid product recovered after reaction Table 3. Summary of experimental data for thermal cracking runs Table 4. Statistical analysis of experimental variation for each kinetic model lump Table 5. Estimated kinetic parameters for Case 1, Case 2 and Case 3 for recycled DAO Table 6. Estimated kinetic parameters for Case 1, Case 2 and Case 3 for virgin DAO Table 7. Kinetic parameters for case 3 - recycled DAO using a 6-lumps kinetic model Table 1. Feedstocks characterization Recycled DAO 6.0

Microcarbon Residue [%wt.]

12.95

Virgin DAO 6.3 12.96

Sulfur [% wt.] Nitrogen [% wt.] Nickel [ppm] Vanadium [ppm] Viscosity @60°C [cP] Viscosity @100°C [cP]

4.0 0.5 45.4 86.5 5339 300

4.8 0.5 48.3 104.2 N/A 1328

4.0 75.0 20.2 0.7

2.4 76.0 20.8 0.8

Naphtha (28 - 190 °C) [%wt.] Kerosene (190 - 260 °C) [%wt.]

0.2 2.7

Diesel (260 - 343 °C) [%wt.]

5.3

0.00 0.00 0.00

LVGO (343 - 453 °C) [%wt.]

7.0

0.6

HVGO (453 - 560 °C) [%wt.] Vacuum Residue (560°C+) [%wt.]

17.2 67.7

12.6 86.8

Analysis API Gravity

SARA

Cut Yields

Saturates [%wt.] Aromatics [%wt.] Resins [%wt.] Asphaltenes-C5 [%wt.]


45

Energy & Fuels

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Energy & Fuels

Table 2. Effect of pressure on recycled DAO thermal cracking. Results reported for the whole liquid product recovered after reaction

Pw 1

Pw 2

300 7.5 0 98.6 40.0 1.15

300 5.0 12.8 98.0 41.0 1.15

Condition Pw 3 Pt1 423 2 300 150 2.5 5.0 25.6 0 97.5 97.1 39.4 40.9 1.15 1.10

13.3 67.3 6.8 12.7

11.6 69.0 7.2 12.3

10.0 67.3 8.7 14.0

12.7 64.9 7.8 14.6

12.4 65.6 7.1 14.9

11.9 62.6 11.4 14.1

8.9 16.57 2080

8.6 16.24 2863

7.8 16.89 2899

8.6 16.82 3011

8.4 16.62 2802

8.1 16.54 2802

Analysis Temperature [°C] LHSV [h-1] Pressure [psig] Water content [%wt.] N2 injected @rxn conditions [mL/min] HC Mass Balance [%] Conversion HC (560 °C+) [%] P-value SARA

Saturates [%wt] Aromatics [%wt] Resins [%wt] Asphaltenes-C5 [%wt]

API Gravity MCR [%wt] Viscosity @25°C [cP]

Pt2

Pt3

225 5.0 0 98.0 38.2 1.10

300 5.0 0 98.9 43.3 1.15


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Page 48 of 51

Table 3. Summary of experimental data for thermal cracking runs

No.

T

LHSV

[°C]

[h ]

Recycled DAO

Virgin DAO

HC Mass

Conversion

HC Mass

Conversion

Balance [%]

[%]

Balance [%]

[%]

0.75

98.9

17.1

0.50

100.0

21.0

3

0.25

99.2

29.2

4

2.0

100.6

29.6

1.5

99.7

31.8

6

1.0

96.5

39.1

99.0

45.2

7

2.5

97.9

32.7

99.7

36.2

2.0

98.6

37.1

9

1.5

99.5

39.9

98.8

45.6

10

3.0

97.4

36.7

101.3

40.7

2.5

99.5

39.5

2.0

98.9

43.3

1 2

5

8

11

380

-1

409

416

423

12

N/A

98.7

32.7 N/A

N/A

N/A 99.7

48.2

Table 4. Statistical analysis of experimental variation for each kinetic model lump Condition 1 Lump [% wt.] Gases Naphtha (28 - 190 °C) Kerosene (190 - 260 °C) Diesel (260 - 343 °C) LVGO (343 - 453 °C) HVGO (453 - 560 °C) DAO (560°C+) Asphaltenes-C5 Vacuum Residue (560°C+)

Condition 2

Average

Standard Deviation

Relative Variance [%]

4.3 8.0 8.5 12.4 15.1 19.5 16.1 16.1 32.2

0.04 0.31 0.06 0.17 0.29 0.81 1.55 0.78 0.86

0.9 3.9 0.8 1.4 1.9 4.1 9.6 4.9 2.7

Average

3.7 6.2 5.9 9.6 13.1 20.1 29.4 11.9 41.3

Standard Deviation

Relative Variance [%]

Average Relative Variance [%]

0.05 0.73 0.58 0.39 0.17 0.27 0.83 0.53 0.34

1.2 11.8 9.9 4.0 1.3 1.3 2.8 4.4 0.8

1.1 7.9 5.3 2.7 1.6 2.7 6.2 4.7 1.7


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Energy & Fuels

Table 5. Estimated kinetic parameters for Case 1, Case 2 and Case 3 for recycled DAO

Recycled DAO Reaction

Kinetic constants at 423 °C [h-1] Case 1

Case 2

Case 3

Ea

Case 1 Ln(A)

[kJ/mol]

[A in h-1]

r2

Ea

Case 2 Ln (A)

[kJ/mol]

[A in h-1]

r2

Ea

Case 3 Ln (A)

[kJ/mol]

[A in h-1]

r2

r1

DAO (560 C+) → Asp -C5

0.5952

0.5969

0.5975

248

42.27

0.9955

247

42.17

0.9952

246

42.04

0.9953

r2

DAO (560 C+) → HVGO

0.5682

0.4556

0.4003

273

46.53

0.9997

266

45.11

0.9995

235

39.68

0.9994

r3

DAO (560 C+) → LVGO

0.4223

0.3724

0.3686

246

41.74

0.9990

245

41.40

0.9992

239

40.33

0.9992

r4

DAO (560 C+) → Diesel

0.2021

0.1943

0.1985

253

42.25

0.9984

230

38.09

0.9985

240

39.88

0.9988

r5

DAO (560 C+) → Kerosene

0.0525

0.0896

0.0692

230

36.77

0.9998

219

35.40

0.9996

241

38.96

0.9997

r6

DAO (560 C+) → Naphtha

0.0686

0.1333

0.1732

143

22.04

0.9998

215

35.19

0.9988

242

40.03

0.9983

r7

DAO (560 C+) → Gas

0.0965

0.1632

0.1980

177

28.26

0.9998

214

35.09

0.9994

244

40.54

0.9995

r8

HVGO → LVGO

0.5978

0.4202

0.3061

293

50.21

0.9995

307

52.25

0.9996

237

39.85

0.9998

r9

HVGO → Diesel

0.0882

0.1009

0.0933

219

35.43

1.0000

277

45.51

0.9999

240

39.14

0.9999

r10

HVGO → Kerosene

0.1410

0.1272

0.1608

243

39.97

0.9998

259

42.66

0.9998

243

40.21

0.9997

r11

HVGO → Naphtha

0.1789

0.0985

0.0913

307

51.40

0.9995

251

41.10

0.9999

249

40.55

0.9999

r12

HVGO → Gas

0.1523

0.1452

0.1221

284

47.15

0.9999

245

40.46

0.9999

260

42.81

0.9999

r13

LVGO → Diesel

0.1402

0.1692

0.1549

202

33.00

1.0000

342

57.36

0.9999

241

39.76

1.0000

r14

LVGO → Kerosene

0.3707

0.2735

0.2978

217

36.43

0.9998

302

50.86

0.9998

245

41.08

0.9999

r15

LVGO → Naphtha

0.4268

0.2913

0.1476

341

58.18

0.9995

289

48.77

0.9998

255

42.07

1.0000

r16

LVGO → Gas

0.4225

0.1119

0.0564

341

58.16

0.9998

277

45.63

1.0000

299

48.85

1.0000

kglobal=2.0054

GAAE[%] = 6.72

GAAE[%]=7.00


49

GAAE[%]=7.02

Energy & Fuels

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Page 50 of 51

Table 6. Estimated kinetic parameters for Case 1, Case 2 and Case 3 for virgin DAO Virgin DAO Reaction r1

Kinetic Constants at 423 °C [h-1] Case 1

Case 2

Case 3

DAO (560 C+) → Asp -C5

0.3125

0.3133

Case 1 Ln A

Ea [kJ/mol]

[A in h-1]

0.3118

228

38.20

r2

Case 2 Ln A

Ea [kJ/mol]

[A in h-1]

0.9998

229

38.45

r2

Case 3 Ln A

Ea

r2

[kJ/mol]

[A in h-1]

0.9998

226

37.95

0.9998

r2

DAO (560 C+) → HVGO

0.6048

0.6095

0.5757

216

36.87

0.9982

239

40.89

0.9986

214

36.49

0.9984

r3

DAO (560 C+) → LVGO

0.4306

0.4381

0.4461

212

35.74

0.9990

222

37.60

0.9991

224

37.93

0.9991

r4

DAO (560 C+) → Diesel

0.2186

0.2041

0.2073

210

34.80

0.9997

215

35.59

0.9997

228

37.89

0.9997

r5

DAO (560 C+) → Kerosene

0.0780

0.0778

0.0781

240

38.89

0.9999

211

33.92

0.9999

235

38.05

0.9999

r6

DAO (560 C+) → Naphtha

0.0768

0.0643

0.0747

267

43.60

0.9999

208

33.13

0.9999

245

39.66

0.9999

r7

DAO (560 C+) → Gas

0.1163

0.1306

0.1438

342

57.01

0.9999

204

33.20

0.9997

262

43.27

0.9998

r8

HVGO → LVGO

0.5904

0.6198

0.4951

219

37.27

1.0000

301

51.48

1.0000

218

36.97

1.0000

r9

HVGO → Diesel

0.1737

0.2246

0.2036

249

41.20

1.0000

239

39.80

1.0000

223

36.96

1.0000

r10

HVGO → Kerosene

0.2736

0.2884

0.2843

218

36.28

1.0000

217

36.23

1.0000

229

38.31

1.0000

r11

HVGO → Naphtha

0.3210

0.2916

0.3532

238

40.01

1.0000

202

33.71

1.0000

238

40.11

0.9999

r12

HVGO → Gas

0.1401

0.0865

0.0995

118

18.39

1.0000

185

29.51

1.0000

279

45.94

1.0000

r13

LVGO → Diesel

0.2094

0.2509

0.2609

291

48.69

1.0000

346

58.32

1.0000

227

37.92

1.0000

r14

LVGO → Kerosene

0.4335

0.4401

0.4542

187

31.50

1.0000

292

49.57

1.0000

237

40.16

1.0000

r15

LVGO → Naphtha

0.5788

0.7458

0.5751

177

30.11

1.0000

260

44.65

0.9999

252

42.97

1.0000

r16

LVGO → Gas

0.1566

0.0435

0.0480

123

19.39

1.0000

205

32.24

1.0000

314

51.28

1.0000

kglobal =1.8376

GAAE[%]=7.01

GAAE[%]=6.62


50

GAAE[%]=7.03

Page 51 of 51

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Energy & Fuels

Table 7. Kinetic parameters for case 3 - recycled DAO using a 6-lumps kinetic model Reaction

r1 r2 r3 r4 r5 r6 r7 r8

DAO (560 °C+) → Asp-C5 DAO (560 °C+) → VGO DAO (560 °C+) → Distillates DAO (560 °C+) → Naphtha DAO (560 °C+) → Gas VGO → Distillates VGO → Naphtha VGO → Gases

k at 423 °C [h-1]

Ea [kJ/mol]

Ln A [A in h-1]

0.5940 0.7900 0.3004 0.1112 0.2098 0.2681 0.2062 0.0787

247 238 239 241 244 239 244 277

42.08 40.85 40.14 39.20 40.63 40.06 40.69 45.46

GAAE [%]

8.20


51

Reactivity and Comprehensive Kinetic Modeling of Deasphalted

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