Experimental Evaluation and Kinetic Modeling of Thermal Upgrading

Jun 24, 2019 - ... products which are heavier than the virgin crude oil. Also, a new approach to kinetic modeling of thermal upgrading processes is pr...
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Cite This: Ind. Eng. Chem. Res. 2019, 58, 12586−12592

Experimental Evaluation and Kinetic Modeling of Thermal Upgrading of Iranian Heavy Crude Oil Paria Sazandehchi and Saeed Ovaysi*

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Faculty of Petroleum and Chemical Engineering, Razi University, Tagh-e Bostan, 67144-14971 Kermanshah, Iran ABSTRACT: Thermal upgrading of Iranian heavy oil is studied on a laboratory scale. A setup is built to mimic the temperature profiles experienced in industrial cracking apparatus. Normally, raising the feed temperature from 340 to 440 °C requires a temperature profile spanning over 10−20 min in an industrial setting. This includes the residence time required for thermal cracking. In this study, it is observed that, through thermal upgrading, API gravity and kinematic viscosity are improved by 67% and 13×, respectively. Additionally, it is observed that temperature profiles leading to long residence times at temperatures below 400 °C yield products which are heavier than the virgin crude oil. Also, a new approach to kinetic modeling of thermal upgrading processes is presented. The new kinetic model takes into account both thermal cracking and poly condensation reactions through a set of 16 chemical reactions. Also, the new approach accounts for variations in reactor temperature and hence more applicable for industrial purposes. Using a hybrid optimization scheme, it is concluded that only 6 thermal cracking and 3 poly condensation reactions significantly affect the thermal upgrading process.

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INTRODUCTION Unconventional heavy oil reserves are increasingly important due to dwindling conventional resources. In the absence of a readily available diluent, utilization of these reserves is usually made possible through a preliminary upgrading step. This upgrading often involves a mild thermal cracking process whereby enhancements are made on viscosity and pour point of the produced oil. In addition to improving the mentioned transport properties, thermal cracking imparts higher yields of straight run distillates to the heavy oil. Thermal cracking is accomplished through a series of free radical chain reactions at temperatures above 350 °C which start by an initiation step and proceed through propagation and termination steps. It is proven that cleavage of C-C bonds at or close to the aryl-alkyl position produces most of the reaction products during the process.1 Furthermore, for structurally similar compounds C-S bonds have low dissociation energies.2 Therefore, the above-mentioned chain reactions in sulfur compounds will probably continue after cleavage of C-S or S-S bonds yielding H2S and mercaptans in the process.3 It has to be stressed that all the available thermal cracking processes allow only a limited amount of time for the chain reactions to proceed, see ref 4. Further exposure of reaction products to moderate temperatures, i.e., below 350 °C, promotes poly condensation reactions which form heavy compounds in contrast to the objectives of upgrading processes. It is known5 that at high reaction temperatures, i.e., above 400 °C, higher conversions of heavy fractions to lighter fractions can be achieved before the onset of coking. Also, it is understood that long residence times at a given reaction temperature increases the yield of heavy fractions. Perhaps, this is caused by poly condensation reactions which © 2019 American Chemical Society

accelerate once free radicals become available after initial cracking of heavy fractions. A recent publication6 highlights how poly condensation reactions can accelerate at moderate reaction temperatures leading to production of heavy fractions. This is corroborated by other findings, e.g., see ref 7. Residence time and reaction temperature are the operating conditions that greatly influence the outcomes of upgrading processes. Optimum values of these parameters are usually determined based on reaction kinetics obtained experimentally so that a desired conversion and product distribution is achieved. Therefore, successful implementation of any thermal cracking process requires a reasonable knowledge of reaction kinetics for the specific feed at hand. Kinetic parameters for thermal cracking of selected compounds are already available in various publications.8−11 In addition to that, upgrading experiments on some specific heavy oils have yielded useful information regarding their kinetic parameters.12−20 In these studies the whole spectrum of feed and possible products is discretized into few pseudocomponents (lumps) based on boiling range or molecular structure of the involved components. The heavier pseudocomponents are then assumed to follow a set of serial/parallel reactions to form lighter pseudocomponents. Two points are important to consider when using the previously reported kinetic parameters as predictive tools. First, poly condensation reactions are overlooked in previously reported kinetic modeling studies even though their contribution to final Received: Revised: Accepted: Published: 12586

March 11, 2019 June 12, 2019 June 24, 2019 June 24, 2019 DOI: 10.1021/acs.iecr.9b01361 Ind. Eng. Chem. Res. 2019, 58, 12586−12592

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Industrial & Engineering Chemistry Research product distributions is known.21 In doing so, kinetic parameters of poly condensation reactions are lumped into those of cracking reactions. Although, under normal process conditions these apparent kinetic parameters can perform well, their predictive capabilities under process upsets and unusual process conditions is not known. As pointed out earlier, poly condensation reactions become dominant at moderate temperatures, and hence influence the products distribution especially if quenching of the products is not perfect. Therefore a general kinetic modeling approach to separately account for both cracking and poly condensation reactions is missing. Second, impact of temperature profile is not included in previous studies. In thermal cracking, the cold feed stream has to follow a temperature profile before reaching the final desired temperature. This is true regardless of whether the process operates at an industrial or laboratory scale. Knowing that the set of serial/parallel reactions advance differently at various temperatures, failure to include temperature profiles in kinetic modeling efforts would result in unpractical kinetic parameters. This is important because most kinetic model parameters are obtained from experiments on batch reactors where heating and cooling of reactor contents can take considerable time. In this study, an experimental setup is designed to carry out thermal cracking experiments on Iranian heavy crude oil. After analyzing the experimental results, a new scheme is presented to include impact of temperature profile on kinetic modeling studies. Furthermore, the proposed reaction set highlights both cracking and poly condensation reactions. On a practical level, this adds the capability to predict off spec products if the thermal upgrading process does not advance as planned.

The feed stock used in all experiments is an Iranian heavy crude oil with the specifications outlined in Table 1. Table 1. Specifications of the Feed Stock property

value

standard deviation

API ν100°C (cSt) pour point (°C) asphaltenes (wt %) total sulfur (wt %) vanadium (mg/kg) nickel (mg/kg)

14.63 31.2 −9 10.14 3.92 50 13

0.20 0.31 0.11 0.14 0.05 0.92 0.12

Experiments start by charging a measured amount of feed stock to the reactor. After placing the reactor inside the furnace, a predetermined temperature profile is applied and variations of temperature and pressure are recorded over time. It has to be mentioned that during the early stages of heating, valves 8 and 9 are left open. This allows the rising hydrocarbon gases to sweep the reactor and remove any pockets of air inside the system. Temperature of the rising gases is continuously monitored and only the very light fractions are allowed to exit the reactor. This is done by closing valves 8 and 9 once T2 reaches 100 °C. Upon finishing the desired temperature profile, the furnace is turned off and the reactor is removed and immersed in a cold bath. Simultaneously, both valves 8 and 9 are turned open to allow recovery of light ends in vessel 7. After reaching temperatures below 10 °C, the reactor contents are discharged and weighed for later analysis. It has to be mentioned that, the test results presented below are obtained for whole products, i.e., the light and heavy products of each experiment are mixed and analyzed as a single product. Also, all experiments are performed at very low ambient temperatures, i.e., below 8 °C. This, in addition to low reactor temperatures, leads to insignificant gas yields. Therefore, mass balance of every experiment points to undetectable gas production. Several experiments are performed to assess the impact of various temperature profiles on progress of cracking/poly condensation reactions occurring during thermal upgrading experiments. Based on the observed temperature profiles, seven experiments emerge as representatives. Each of these experiments are performed in triplicate using identical procedures leading to quite similar temperature profiles. Figure 2 shows variation of reactor temperature for these experiments over time. Clearly, different temperature profiles are observed in each test. It has to be noted that, based on our experiments, prolonged exposure to temperatures above 420 °C leads to production/agglomeration of asphaltene molecules for this type of crude oil. Therefore, to prevent coke formation,1 it is tried to avoid such temperature profiles. Analyses. Distillations were performed using a Petrotest ADU4 according to ASTM D86 standards. Viscosity was measured using Cannon-Fenske viscometers in a petrotest 40E oil bath conforming to ASTM D445. API gravity measurements were performed according to ASTM D1298 using hydrometers from Fisher Scientific. Pour points were measured using a petrotest CAPP equipment according to ASTM D97 standard. Total sulfur and metals contents measurements were performed by an outside laboratory according to ASTM D4294 and ASTM D5863 standards, respectively. Asphaltene contents were measured by precipitating the n-pentane

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EXPERIMENTAL SECTION Setup and Procedure. The experiments are performed in a setup consisting a 567 mL reactor made from 3 in. carbon steel pipe placed inside a gas furnace with fire brick refractory walls, cf. Figure 1. A long type K thermocouple is used to

Figure 1. Experimental setup. (1) Reactor thermocouple, (2) rising gases thermocouple, (3) pressure gauge, (4) furnace, (5) reactor, (6) condenser, (7) gathering vessel, (8) gathering valve, (9) to vent valve, and (10) charging/discharging valve.

monitor liquid temperature inside the reactor. This thermocouple is placed halfway between center and side walls of reactor to give an average reading for the liquid phase temperature. Although, given the small size of the reactor, temperature variations within the liquid phase are assumed to be negligible. Rising gases from the reactor pass over another thermocouple before being cooled by a 1 m long double tube heat exchanger. As shown in Figure 1, flow of rising gases is controlled by a valve. Additionally, a pressure gauge is used to monitor reactor pressure. 12587

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in spite of the improved API gravity for this test. We believe the poly condensation reactions are to be blamed for such discrepancies. As shown in Figure 2, the temperature profiles observed in tests 4 and 7 are less intense and hence the produced free radicals are less likely to have high energies. Therefore, the chances of these free radicals joining together and producing heavier products is high under less intense temperature profiles. This is in accordance with the findings reported elsewhere.6 Furthermore, products of this type of reaction are more paraffinic as indicated by high viscosity and API gravity of products of tests 4 and 7. Knowing that paraffins exhibit higher pour points, the above statement is further confirmed by observing increased pour points for products of tests 4 and 7 compared to that of the virgin heavy oil. Comparing asphaltene contents of products to that of the virgin heavy oil, it is evident that in all tests asphaltenes are produced. However, no agglomeration/precipitation of asphaltenes is noticed 2 months after the experiments. Observing coke productions in tests 2 and 6, we conclude that only prolonged exposure to high temperatures, as observed by the temperature profiles of these tests in Figure 2, can yield coke. Conversion is defined based on mass fraction of the heaviest pseudocomponent present in the products versus that in the feed stock, i.e.,

Figure 2. Various temperature profiles observed during experiments.

insolubles from the samples. The procedure is similar to what is described in refs 5 and 6 based on ASTM D2007 standard. Approximately, 5 g of samples were mixed with 200 mL of npentane. The solution was then mixed for 1 h in ambient conditions using a stirrer and left for a minimum of 10 h to allow for better agglomeration/precipitation of asphaltenes. The precipitates were then separated by vacuum filtration using a 0.22 μm filter and left to dry for a minimum of 2 days in a fume hood. Asphaltene contents were obtained by dividing the net mass of dry precipitates to the exact mass of initial oil samples measured up to 0.001 g. An identical procedure was used to measure coke content of the samples except for using methylene chloride instead of n-pentane and performing the experiments on the entire reactor contents. All experiments were performed in triplicate and standard deviations were calculated. Results and Discussion. Table 2 presents a summary of experimental conditions as well as bulk properties of products for the seven representative tests. Compared to the analysis in Table 1, it is clear that all the cracked products are less dense which is indicated by their increased API gravities. Although, quite expectedly, more intense temperature profiles observed in tests 1, 2, 5, and 6 yield much lighter products. Additionally, these temperature profiles produce products that are less viscous and hence easier to transport than the virgin crude oil. Tests 4 and 7 shed light on the impact of improper temperature profiles on thermal cracking reactions. The results presented in Table 2 indicate a higher viscosity for products of tests 4 and 7 compared to that for the virgin crude oil. This is

X=

C4,feed − C4,product C4,feed

(1)

where X denotes conversion. Observing the conversions in Table 2, we note that the temperature profile in test 6 leads to favorable combination of residence time and reaction temperature to achieve the highest conversion among all tests performed. On the other hand, temperature profiles in tests 3, 4, and 7 achieve negative conversions which as discussed above is due to poly condensation reactions. To support the above statements, in Figure 3 pressure profiles are plotted for all tests. As shown, pressure increases slowly at the early stages of process which indicates a slight progress of thermal cracking reactions. However, over time lighter hydrocarbons evolve to increase the reactor pressure at a much faster pace once temperature increases. It is also clear that thermal cracking reactions progress just a little during tests 3 and 7. This is even more highlighted for test 4 where the produced free radicals immediately combine to form even heavier hydrocarbons. Therefore, no increase in pressure is observed during this test. It has to be pointed out that the sudden pressure drops at the end of experiments is due to quenching of reactor contents and opening of valves 8 and 9 in

Table 2. Summary of Experimental Conditions and Bulk Properties of Products for the Seven Representative Testsa test number property

1

2

3

4

5

6

7

T350+,ave (°C) t350 (min) API ν100°C (cSt) asphaltene (wt %) pour point (°C) Coke (wt %) X (%)

405.2 40.5 19.37(0.12) 8.7(0.08) 11.22(0.1) −18(0) 0(0) 15.66

407.4 43.8 21.97(0.10) 7.8(0.06) 11.72(0.1) −18(0) 0.12(0.04) 11.94

382.1 23.5 16.51(0.14) 24.2(0.12) 10.56(0.09) −12(0) 0(0) −16.02

373.2 14.8 17.20(0.13) 36.4(0.11) 10.44(0.10) −6(0) 0(0) −3.97

387.2 30.0 20.65(0.12) 6.4(0.06) 11.56(0.09) −15(0) 0(0) 3.52

411.2 45.2 24.51(0.10) 2.4(0.05) 12.18(0.10) −21(0) 0.36(0.07) 19.40

382.3 20.8 17.86(0.12) 32.3(0.11) 10.52(0.10) −9(0) 0(0) −1.82

a

Numbers in parentheses indicate standard deviations. 12588

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less favorable to thermal cracking reactions and as such produce less free radicals. Similar to the above argument, these free radicals produce heavy compounds too. However, the extent of free radicals and thus heavy compounds formation is smaller in test 4 compared to tests 3 and 7. Please also see refs 6, 7, and 21 for similar findings. To prepare the results for kinetic modeling studies, mass of the condensed phase was weighed during all the above distillation tests. This results in Figure 5 where boiling

Figure 3. Pressure variations during experiments.

Figure 1. The closed system in this study allows only a limited amount of light materials to vaporize as further vaporization leads to increased pressure and hence condensation of the vapor phase in the reactor. Therefore, the amount of light materials in the vapor phase is expected to stay constant for all tests. To further investigate the reaction paths during thermal upgrading experiments, a series of ASTM D86 distillation tests were performed on the virgin crude oil as well as products of the above seven representative tests, see Figure 4. As expected,

Figure 5. Modified results of ASTM D86 tests on the virgin crude oil and the upgraded products of the seven representative tests.

temperature is plotted against mass percent of the distilled product. Furthermore, using this figure, the entire boiling range was discretized into four pseudocomponents roughly representing the straight run products of a typical atmospheric distillation tower as shown in Table 3. Figure 6 illustrates distribution of these four pseudocomponents for the virgin crude oil as well as the upgraded products in tests 1 through 7.

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KINETIC MODELING. As shown in Table 4, both thermal cracking and poly condensation reaction sets are assumed to take place during the thermal upgrading experiments discussed above. The sets of reactions presented in Table 4 are studied to include all possible reactions that might take place during a thermal cracking operation. Below, we show that only few of these reactions are significant. Reaction rates ki are given by the Arrhenius equation.

Figure 4. Results of ASTM D86 test on the virgin crude oil and upgraded products of the seven representative tests.

tests 1, 2, 5, and 6 which experienced more intense temperature profiles result in products that are lighter and yield higher fractions of light and middle distillates. Whereas, tests 3, 4, and 7 result in heavier products and lower yields of light and middle distillates. Interestingly, test 3 results in a heavier product than that of test 4 despite experiencing a rather more intense temperature profile. This is explained by the fact that at the relatively high temperatures experienced during test 3 a larger portion of the feed stock is cracked and converted to free radicals. However, the free radicals thus produced do not have enough energy and therefore, as noted earlier, combine together to form heavier compounds which is clearly illustrated in Figure 4. Temperature profiles experienced during test 4 are

ki = Ai e(−Ei /RT)

(2)

The ultimate goal of the kinetic modeling effort presented in this section is to obtain pre-exponential term Ai and activation energy Ei for any reaction i presented in Table 4. The governing equations of the system under study is obtained using mass balance for each of the four pseudocomponents C1 through C4, i.e., dC4 = −(k1 + k 2 + k 3)C4 + k 9C42 + k11C22 + k12C32 dt + k14C1C2 + k15C1C3 + k16C2C3 12589

(3a)

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Industrial & Engineering Chemistry Research Table 3. Boiling Range and Mass % of the Pseudo-Components C1−C4 in Feed and Upgraded Productsa mass % pseudocomponent

boiling range (°C)

feed

test 1

test 2

test 3

test 4

test 5

test 6

test 7

C1 C2 C3 C4

0−160 160−260 260−310 310+

10.11 16.16 13.26 60.47

13.40 23.79 11.81 51

13.38 19.77 13.60 53.25

8.38 14.19 7.27 70.16

8.92 16.11 12.10 62.87

11.33 16.39 13.94 58.34

16.34 22.69 12.23 48.74

10.77 15.12 12.54 61.57

a

Each experiment was performed three times and average standard deviation for all data points is 0.15.

integration is performed numerically using an Euler scheme with Δt ≈ 10 − 15s. Compared to the 60−80 min length of each experiment, this time step is really small and insignificant variations in temperature are observed during a time step. Therefore, errors in the employed numerical integration scheme is negligible. To perform time integration of eq 3a−3d, the correct values of Ai and Ei are needed for these 16 reactions. Therefore, an objective function is defined based on deviation of the computed mass fractions of pseudocomponents C1 through C4 from those obtained experimentally given the same temperature profile. This deviation is computed separately for each of the four representative tests and summed up to a single objective function, i.e., f (A, E) = (Etest1 + Etest2 + Etest3 + Etest 4 + Etest5 + Etest6 + Etest7)/N Etestk

Figure 6. Distribution of mass fractions of pseudocomponents C1 through C4 for the virgin crude oil and the upgraded products.

(4)

where, vectors are shown in bold face and N is the number of data points, i.e., N = number of tests × number of data points per test = 7 × 4 = 28. Given the above objective function, the problem of finding the correct values for Ai and Ei is simply written in form of the optimization problem below.

Table 4. Sets of Reactions Assumed to Take Place During the Upgrading Experiments category thermal cracking

reactions k1

k4

C4 → C3

k6

C2 → C1

C3 → C2

k2

Min. f (A, E)

l A, E ≥ 0 o o o o o E1 ≤ E2 ≤ E3 ≤ E4 ≤ E5 ≤ E6 s. t . : m o o o o o E7 = E8 = E9 = ... = E16 = 0 n

k5

C4 → C2

C3 → C1

k3

C4 → C1 poly condensation

k7

2C1 → C2 k8

2C1 → C3

k10

2C2 → C3

k12

2C3 ⎯→ ⎯ C4

k11

2C2 → C4

k9

2C1 → C4 k13

C1 + C2 → C3 k14

C1 + C2 ⎯→ ⎯ C4

k16

C2 + C3 → C4

dC 3 = k1C4 − (k4 + k5)C3 + k 8C12 + k10C22 − 2k12C32 dt (3b)

dC 2 = k 2C4 + k4C3 − k6C2 + k 7C12 − 2(k10 + k11)C22 dt − (k13 + k14)C1C2 − k16C2C3

(3c)

dC1 = k 3C4 + k5C3 + k6C2 − 2(k 7 + k 8 + k 9)C22 dt − (k13 + k14)C1C2 − k15C1C3

(5)

(6)

The constraints on activation energies are placed based on previous studies,21 where activation energies for cracking of heavy fractions are lower than those for lighter fractions. Additionally, activation energies for the formation of heavier fractions are lower than those for lighter fractions. Poly condensation reactions where free radicals recombine to form larger compounds are assumed to have zero activation energies.3 Thus, the rate constants for such reactions are independent of temperature. A hybrid of genetic algorithm and sequential quadratic programming optimization techniques is used to solve the above optimization problem. The objective function is found to reach a global minimum at the point elaborated in Table 5 corresponding to f min = 6.81 × 10−4. The computed pre-exponential parameter and activation energies agree well with those reported in earlier publications.17,18,20 To assess quality of the optimum found by the above-mentioned method, in Figure 7 variation of objective function versus deviation of each parameter from optimum is plotted. As shown, zero deviation from optimum yield the lowest amount of objective function. Hence, it is highly likely that the optimum point in Table 5 corresponds to the global minimum of objective function.22 Also, given the temperature profiles

k15

C1 + C3 → C4

+ k13C1C2 − k15C1C3 − k16C2C3

exp 2 exp 2 exp 2 calc calc = (C4,calc k − C4, k ) + (C3, k − C3, k ) + (C 2, k − C 2, k ) exp 2 calc + (C1, k − C1, k )

(3d)

where Cj denotes mass fraction of pseudocomponent j = 1−4. Given a set of Ai and Ei for all of the 16 reactions, the final value of Cj after a certain amount of time can be computed through time integration of eq 3a−3d In this study, time 12590

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Industrial & Engineering Chemistry Research Table 5. Optimum Values of Ai and ki for the 16 Reactions Considered in This Study reaction no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

A (1/s)

E (kJ/mol)

× × × × × × × × × × × × × × × ×

248 249 252 252 252 258 0 0 0 0 0 0 0 0 0 0

4.72 2.38 5.25 1.81 1.69 1.30 9.97 7.07 9.99 3.97 7.85 9.93 6.30 8.74 7.10 4.51

1013 1013 1014 1014 1013 1013 10−7 10−9 10−7 10−9 10−9 10−7 10−9 10−9 10−9 10−9

Figure 8. Comparison of model computed values of pseudocomponent mass fractions versus those obtained by experiments.

Figure 9. Reaction rate constants at 300 and 400 °C for the 16 assumed reactions.

Figure 7. Variation of objective function as A and E deviate from optimality.

atures. However, free radicals must be present in order for these reactions to proceed. Therefore, products of thermal upgrading have to be quickly quenched to stop the progress of poly condensation reactions.

during tests 1 through 7, values of Cis for the four pseudocomponents are calculated using the kinetic parameters in Table 5. To further assess accuracy of the computed kinetic parameters, in Figure 8 calculated values of Cis are compared against those obtained by experiments for their respective temperature profiles. Based on the correlation coefficient R = 0.9926, the computed kinetic parameters are accurate enough to yield numbers which are in good agreement with experiments. Using these kinetic parameters, values of reaction rate constants for the 16 reactions in Table 4 are compared in Figure 9 at 300 and 400 °C. Evidently, all the 6 thermal cracking reactions are important at 400 °C. However, thermal cracking of C4 to C1, i.e., reaction 3 in Table 4, has the highest rate constant. Thermal crackings of C3 to C2 and C4 to C1, i.e., reactions 4 and 1, are the next important reactions, respectively. On the other hand, only formation of C2 and C4 through recombination of C1, i.e., reactions 7 and 9, and formation of C4 through recombination of C3, i.e., reaction 12, are the most important poly condensation reactions. As shown in Figure 9, high temperatures favor thermal cracking reactions. Comparing the rate constants at 300 and 400 °C, it is clear that poly condensation reactions are dominant at lower temper-

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CONCLUSIONS An experimental setup is designed and built to study thermal upgrading of an Iranian heavy crude oil. To simulate the actual temperature profiles experienced by streams of crude oil passing through industrial furnaces, the reactor temperature is allowed to continuously increase over time during each experiment. Out of the 53 exploratory and main thermal upgrading experiments, only 7 are chosen to represent the various temperature profiles. Reaction products as well as the virgin crude oil are further analyzed to obtain their bulk and fractional properties. It is shown that, using thermal upgrading, crude kinematic viscosity, i.e., ν100°C, can reduce from 31.2 to 2.4 cSt (13X reduction) while API gravity can increase from 14.63 to 24.51 (67% improvement). Using fractional analyses, four pseudocomponents are defined roughly based on boiling ranges of straight run atmospheric distillates. Mass fractions of these four pseudocomponents are then measured and used in kinetic modeling. To represent both cracking and poly 12591

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(16) Alvarez, E.; Marroquin, G.; Trejo, F.; Centeno, G.; Ancheyta, J.; Diaz, J. Pyrolysis kinetics of atmospheric residue and its SARA fractions. Fuel 2011, 90 (12), 3602−3607. (17) AlHumaidan, F.; Hauser, A.; Al-Rabiah, H.; Lababidi, H.; Bouresli, R. Studies on thermal cracking behavior of vacuum residues in Eureka process. Fuel 2013, 109, 635−646. (18) 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, 3024−3031. (19) Aguilar, R. A.; Ancheyta, J. Modeling coil and soaker reactors for visbreaking. Ind. Eng. Chem. Res. 2016, 55 (4), 912−924. (20) Zhang, D.; Ren, Z.; Wang, D.; Lu, K. Upgrading of crude oil in supercritical water: A five-lumped kinetic model. J. Anal. Appl. Pyrolysis 2017, 123, 56−64. (21) Cabrales-Navarro, F. A.; Pereira-Almao, P. Reactivity and comprehensive kinetic modeling of deasphalted vacuum residue thermal cracking. Energy Fuels 2017, 31 (4), 4318−4332. (22) Alcazar, L. A.; Ancheyta, J. Sensitivity analysis based methodology to estimate the best set of parameters for heterogeneous kinetic models. Chem. Eng. J. 2007, 128, 85−93.

condensation reactions, 16 reaction paths are proposed. In obtaining the kinetic parameters of these reactions, the impact of time varying reactor temperatures are fully taken into account. The Arrhenius kinetic parameters are obtained by solving a multivariate optimization problem. It is concluded that only 9 reactions (6 thermal cracking and 3 poly condensation) are significant during the thermal upgrading experiments. The kinetic parameters obtained in this study can be used in designing upgrading facilities handling Iranian heavy crude oil.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +98 833 427 4536. Fax: +98 833 427 4536. ORCID

Saeed Ovaysi: 0000-0003-1639-078X Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This study is supported by Iranian Central Oil Fields Company (ICOFC). Their financial support is gratefully acknowledged. REFERENCES

(1) Saxena, A.; Diaz-Goano, C.; Dettman, H. Coking behaviour during visbreaking. Journal of Canadian Petroleum Technology 2012, 51 (06), 457. (2) von Cottrel, T. L. The strengths of chemical bonds; Butterworths Publications Ltd.: London, 1954. (3) Raseev, S. Thermal and catalytic processes in petroleum refining; Marcel Dekker Inc.: New York, 2003. (4) Rana, M.; Samano, V.; Ancheyta, J.; Diaz, J. A. I. A review of recent advances on process technologies for upgrading of heavy oils and residua. Fuel 2007, 86 (9), 1216−1231. (5) Wang, L.; Zachariah, A.; Yang, S.; Prasad, V.; de Klerk, A. Visbreaking oilsands-derived bitumen in the temperature range of 340−400 C. Energy Fuels 2014, 28 (8), 5014−5022. (6) Castillo, J.; de Klerk, A. Visbreaking of deasphalted oil from bitumen at 280−400 C. Energy Fuels 2019, 33 (1), 159−175. (7) Sachanen, A. N. Conversion of petroleum: Production of motor fuels by thermal and catalytic processes; Literary Licensing LLC, 2013. (8) Ranzi, E.; Dente, M.; Pierucci, S.; Biardi, G. Initial product distributions from pyrolysis of normal and branched paraffins. Ind. Eng. Chem. Fundam. 1983, 22 (1), 132−139. (9) Volkan, A. G.; April, G. C. Survey of propane pyrolysis literature. Ind. Eng. Chem. Process Des. Dev. 1977, 16 (4), 429−436. (10) Shah, M. J.; Jose, S. Computer control of ethylene production. Ind. Eng. Chem. 1967, 59 (5), 70−85. (11) Froment, G. P.; de Steene, B. O. V.; Damme, P. S. V.; Narayanan, S.; Goossens, A. G. Thermal cracking of ethane and ethane-propane mixtures. Industrial Engineering Chemistry Process Design and Development 1976, 15 (4), 495−504. (12) 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, 1373−1387. (13) Gray, M. R.; McCaffrey, W. C.; Huq, I.; Le, T. Kinetics of cracking and devolatilization during coking of Athabasca residues. Ind. Eng. Chem. Res. 2004, 43 (18), 5438−5445. (14) 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. (15) Jia, N.; Moore, R. G.; Mehta, S. A.; Ursenbach, M. G. Kinetic modeling of thermal cracking reactions. Fuel 2009, 88 (8), 1376− 1382. 12592

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