Simulation of Petroleum Residue Hydroconversion in a Continuous

Article pubs.acs.org/IECR

Simulation of Petroleum Residue Hydroconversion in a Continuous Pilot Unit Using Batch Reactor Experiments and a Cold Mock-Up Tim Jansen, Dimitri Guerry, Emmanuel Leclerc, Marie Ropars,† Maxime Lacroix,‡ Christophe Geantet, and Melaz Tayakout-Fayolle* IRCELYON, Institut de recherches sur la catalyse et l’environnement de Lyon, UMR5256, CNRS−Université Lyon 1, 2 avenue Albert Einstein, 69626 Villeurbanne, France ABSTRACT: The kinetics of atmospheric petroleum residue hydroconversion with a dispersed catalyst was studied. A methodology has been developed in order to transpose the chemical kinetics (reaction network, stoichiometry, and kinetic constants) obtained with a batch reactor by Nguyen et al. to a continuous reactor [Nguyen, T. S.; Tayakout-Fayolle, M.; Ropars, M.; Geantet, C. Chem. Eng. Sci. 2013, 94, 214]. Their five-lump kinetic model takes into account vapor−liquid mass transfer, vapor−liquid equilibriums, and hydrogen consumption. Consequently, hydrodynamics and vapor−liquid mass transfer of the micropilot unit’s reactor were studied in a cold mock-up by tracer experiments. The same thermodynamic model given by Nguyen et al. was used, and the flash calculations were performed using ProSimPlus software. Experimental data were obtained in the micropilot unit at 420, 430, and 440 °C with a dispersed catalyst for residence times of 1 and 2 h. The catalyst precursor, an oil-soluble molybdenum naphthenate, was added to obtain a molybdenum concentration of 600 wt ppm in the feedstock. The total pressure was 12 MPa with a hydrogen-to-feed ratio of 500 N m3/m3. The methodology was validated by comparing the model’s output with the experimental results.

1. INTRODUCTION Fossil fuels will remain the principal sources of energy worldwide for the near future. The demand for transportation fuels such as gasoline and diesel will continue to grow, most notably in countries with emerging economies.1 With the depletion of the reserves of light crude oils, the valorization of heavy oils and petroleum residues becomes a necessity. However, the refining of these feedstocks is complicated by elevated concentrations of highly aromatic macromolecules, heteroatoms (S, N), and metals (V, Ni).2 In addition, environmental regulations of sulfur content in transportation fuels demand a high level of desulfurization of the oil, for example, 10 ppm for the European Union. Different processes have been developed for the refining of heavy oils and petroleum residues.3 Traditionally, coking has been the process of choice as the costs involved are comparatively small, although the coke produced is a fairly low quality product. Higher liquid product yields as well as high levels of hydrogenation and desulfurization can be obtained by catalytic hydroconversion processes employing Ni−Mo or Co− Mo catalysts supported on alumina. However, asphaltenes and metals are well-known for the deactivation of supported hydrotreating catalysts by pore plugging and active phase deactivation.4 Although much progress has been achieved in recent years in the development of hydroconversion processes, supported catalysts may not be optimal for the refining of the most difficult feedstocks. This led to the development of processes using unsupported, highly dispersed catalysts often called slurry phase processes.5,6 Dispersed catalysts are introduced into the feedstock in the form of a precursor. These are usually solid powders or wateror oil-soluble precursors that contain a transition metal (Mo, Fe, Co, Ni, etc.).7 Oil-soluble, molybdenum containing © 2014 American Chemical Society

precursors are usually preferred because of molybdenum’s strong hydrogenating ability and the high dispersions that are easily achieved when an oil-soluble precursor is used. The active species are finely dispersed MoS2 slabs that are generated in situ. These slabs are about several nanometers in length with a stacking close to 1. Several studies report on the influence of operating conditions such as temperature, pressure, reaction time, metal concentration, nature of catalytic precursor, etc.8−13 As they cannot be deactivated by pore plugging, dispersed catalysts allow hydrogenation and desulfurization of the feedstock while efficiently preventing coke formation even at high conversion. The combination of a supported Co−Mo/γalumina catalyst with a dispersed catalyst gave rather unsatisfying results.14 The authors reported that the dispersed catalyst seemed to form deposits on the supported catalyst, thus deactivating partially the catalyst sites. Recent research, however, showed that dispersed catalysts are able to protect a cracking catalyst from deactivation by coke or metal deposition.15,16 Kinetic modeling of heavy oil and petroleum residue conversion has attracted more and more attention in recent years. As the petroleum mixture is extremely complex, classic kinetic modeling techniques cannot be used and, consequently, different approaches with varying complexity have been developed for the hydrocracking of heavy oil fractions.17 As the analytical and computational techniques evolve to allow a more and more detailed description of the petroleum products, increasingly complex kinetic models can be formulated. Received: Revised: Accepted: Published: 15852

June 4, 2014 September 5, 2014 September 16, 2014 September 16, 2014 dx.doi.org/10.1021/ie502242f | Ind. Eng. Chem. Res. 2014, 53, 15852−15861

Industrial & Engineering Chemistry Research

Article

Figure 1. Methodology of the development of the micropilot unit’s model.

as viscosity, density, and surface tension, is difficult to use to determine RTD with available analytical techniques. Therefore, the water−nitrogen/air system is the most commonly used. Literature regarding physical characterization of continuous stirred tank reactors (CSTRs) for petroleum applications is scarce, although numerous studies can be found for bioreactors.32 Kinetic modeling of the petroleum residue hydroconversion with dispersed catalysts has been studied early by Del Bianco et al.33 by means of a simple two-lump model. Panariti et al. then developed a four-lump model that includes hydrogen consumption. The aim was to distinguish between thermal cracking and catalytic hydrogenation reactions.34 The five-lump kinetic model from the work of Sanchez et al.19 has been adapted in several kinetic studies of the Athabasca bitumen conversion at low severity35−37 as well as for the upgrading of a vacuum residue by aquaprocessing.38 A five-lump kinetic model developed by Nguyen et al. at IRCELYON in collaboration with Total Refining and Chemistry takes vapor−liquid equilibriums as well as hydrogen consumption.39 The kinetic model plays an important role in the development of an industrial process. No literature can be found where kinetic data are used for the prediction of petroleum residue conversion performed on another unit. The aim of this work was thus to transpose a kinetic model developed on a batch reactor onto a continuous micropilot unit. The methodology is presented in Figure 1. The kinetic model derived from batch reactor experiments39 is coupled with hydrodynamics and mass transfer characteristics determined on a cold mock-up of the micropilot unit. Vapor− liquid equilibriums are calculated using ProSimPlus software based on the experimental results obtained in the micropilot unit. The approach as well as the kinetic model would be validated by comparing the model’s output with experimental data.

However, most published kinetic studies still employ the relatively simple lumping approach. For example, a lump can be defined with respect to its solubility properties in different solvents or correspond to a boiling point range. The number of lumps varies from study to study. The simplest model would consist of only two lumps: a residue and a distillate fraction. The number of lumps may increase to three or four, when gas and coke productions are significant.18,19 For a more detailed analysis of the liquid products, it is convenient to cut up the hydrocarbon mixture into different lumps using boiling point ranges. Sanchez et al.20 developed a five-lump kinetic model with 10 possible reaction pathways that was used as a basis for several authors. Complex reaction networks can be simplified by estimating all constants and then eliminating negligible kinetic constants,21 whereas another strategy is to eliminate reaction pathways beforehand by DELPLOT analysis.22 For a more accurate description of the intrinsic kinetics, vapor−liquid equilibrium, hydrodynamics, and mass transfer characteristics need to be taken into account.23 The associated physical parameters of the reactor such as the gas holdup and the mass transfer coefficient are generally determined from experimental measurements. Experimental measuring techniques in gas−liquid and gas−liquid−solid reactors have been reviewed by Boyer et al., by classing them into invasive and noninvasive techniques.24 Tracer experiments are used to determine the residence time distribution (RTD), which characterizes the hydrodynamic behavior globally. However, during the scale-up process of the reactor, additional local data may be necessary to complement the global hydrodynamic characterization. In this field, computational fluid dynamics is a promising tool.25,26 In situ characterization of hydrodynamics and mass transfer of reactors operating at high pressure and high temperature require expensive methods. For example, Kressmann et al. conducted an RTD study of a pilot unit of the H-Oil process using a radioactive tracer,27 which led to the development of a five-lump kinetic model including hydrogen.28 In general, however, the characterization of the reactor under operating conditions is based on cold flow mock-ups. These latter operate at ambient conditions and use fluids with physical properties similar to the reaction mixture under operating conditions. For example, cold mock-ups have been used for scale-up of the bubble column Fischer−Tropsch process.29−31 The fluid that represents all key parameters, such

2. EXPERIMENTAL SECTION 2.1. Batch Reactor Experiments. Only the relevant operating conditions of the batch reactor experiments are presented. More details can be found in the original publication.39 Hydroconversion experiments were performed in a 250 cm3 bench-scale batch reactor. In each experiment 100 g of an Arabian light atmospheric residue (AR) was mixed with 15853

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studied. The gas composition was analyzed by gas chromatography. The gas was quantified using 2 vol % N2 in H2 as an inert tracer. The liquid reaction products are sampled continuously and recovered quantitatively during steady state. Experimental mass balances were 95 ± 5%. Some of the hot separator bottom liquid product (HSB) was lost during the sampling process. Consequently, losses were attributed to the hot separator bottom product in order to complete the mass balance. A detailed description of the microscale pilot unit as well as the experimental procedures can be found elsewhere.40 Density of the liquid products was analyzed on a Mettler Toledo DR40 combined meter. Liquid products were analyzed by simulated distillation done on an Agilent 6890 series gas chromatograph. The column was a Restek MXT-1HT 5 m × 0.53 mm i.d. × 0.10 μm. The method was based on the ASTM D7169 norm. Based on the resulting curve, the liquid products were defined by the same four boiling point ranges defined by Nguyen et al.:39 NAPH, 40−180 °C; DIST, 180−350 °C; VGO, 350−510 °C; and RES, 510 °C+. The conversion of the RES fraction is defined as follows:

an oil-soluble catalytic precursor (molybdenum naphthenate, 9 wt % Mo, The Shepherd Chemical Company) to obtain a concentration of 600 wt ppm of Mo. Some properties of the AR can be found in Table 1. Dimethyl disulfide (DMDS) was Table 1. Properties of the Arabian Light Atmospheric Residue Feedstock parameter physical properties viscosity at 100 °C (cSt) density at 15 °C (g·cm−3) elemental analysis (wt %) C H N S V + Ni (wt ppm) H/C atomic ratio (mol/mol) boiling point ranges (wt %) NAPH (40−180 °C) DIST (180−350 °C) VGO (350−510 °C) RES (510 °C+)

28.9 0.958 85.3 11.4 0.2 2.8 62.7 1.60 0 5.7 42.3 52.0

conv 510 °C+ (wt %) =

Yj (wt %) =

reaction temp (°C)

residence time (h)

420 430 440 420 430 440

0.94 0.94 0.94 1.88 1.88 1.88

·100 (1)

Q mj ,out Q mfeed

·100 (2)

As shown in Figure 1, the experimental data gathered from this study were utilized to calculate inlet and outlet flows of the continuous pilot unit model. 2.3. Cold Mock-Up Experiments. Hydrodynamic behavior and the volumetric mass transfer coefficient of the continuous pilot unit were based on the results obtained from the cold mock-up (cf. Figure 1). A simplified scheme of this cold mock-up is given in Figure 3. The cold mock-up operates at atmospheric pressure and is equipped with a cooling jacket to keep the temperature constant at 20 °C. The pilot unit’s liquid and vapor phases are replaced in the cold mock-up with water and nitrogen, respectively, under the assumption that their relevant physical properties are similar under the respective operating conditions. Hydrodynamics and mass transfer were studied using tracer experiments. Because of the small reactor size, the evolution of the tracer concentration could not be followed inside the stirred tank. Instead, transit chambers fitting to probes had been manufactured in order to minimize the surrounding volume. A more detailed description of the cold mock-up is given by Jansen et al.40 The hydrodynamic behavior of the stirred tank and gas holdup were determined using a nontransferable tracer (NaCl) between the liquid phase and the gas phase in order to obtain the residence time distribution (RTD) of the liquid phase. The detailed procedure and the results are described elsewhere.40 Mass transfer characteristics were studied using a transferable tracer between the liquid phase and the gas phase (O2).41−43 The probe chamber separates gas and liquid flows in order to have only liquid in contact with the oxygen probe and to ensure its proper operation. Inlet gas was switched from nitrogen to air after the system had reached steady state. The evolution of the oxygen concentration in the liquid phase was followed with a

Table 2. Operating Conditions for the Different Runs 1 2 3 4 5 6

Q mRES,in

The yield of each lump j is calculated with respect to the mass flow rate of the feedstock Qmfeed.

added to facilitate the sulfidation of Mo. The reactor was pressurized with 9 MPa of hydrogen at room temperature, which would rise to approximately 15 MPa at operating conditions. The AR was converted at 420 and 430 °C for reaction times of 0, 30, 45, and 60 min. The experimental data obtained were used to develop a kinetic model for the batch reactor.39 As shown in Figure 1, the kinetic model of the continuous pilot unit described in this work is based on the batch reactor study. 2.2. Micropilot Unit Experiments. Hydroconversion of the AR was performed at a total pressure of 12 MPa for temperatures of 420, 430, and 440 °C for residence times of 0.94 and 1.88 h. The operating conditions of the six different runs are summarized in Table 2.

run no.

Q mRES,in − Q mRES,out

Residence time was calculated as the total reactor volume without internals (Vtot = 33 cm3) divided by the feedstock inlet flow rate. The hydrogen-to-feed ratio was 500 N m3/m3. The AR was previously mixed with molybdenum naphthenate in order to obtain a Mo concentration of 600 wt ppm. DMDS was added to ensure the sulfuration of the Mo. Figure 2 presents a simplified scheme of the micropilot unit. The unit consists of a 33 cm3 continuous stirred tank reactor (CSTR), a 20 cm3 high temperature, high pressure separator (400 °C), and a 20 cm3 low temperature, low pressure separator (20 °C). The feedstock tank as well as most of the tubing is kept inside an oven at a temperature of 160 °C. Solid precipitation was not observed in the operating condition range 15854



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Figure 2. Schematic drawing of the micropilot unit.

the AR conversion in the micropilot unit. Thus, the same set of model assumptions was used. Uniform liquid and vapor phases were assumed (verified in the cold mock-up) as well as a uniform distribution of the catalyst particles. The latter assumption is justified as the catalyst particles are of submicrometer size.8,9,11,13 Thus, a two-phase liquid−vapor system has been considered. Reactions are supposed to take place only in the liquid phase of the stirred tank reactor. The impacts of reactions that may take place in the hot separator were supposed to be negligible considering the short residence time (about 20 min) and the temperature of 400 °C. All the reactions were supposed to be first order with respect to the lumps as well as with respect to the hydrogen concentration. Hydrogen has been considered a co-reactant, in order to account for its consumption and to determine “semi-intrinsic” kinetic constants. Consequently, the model takes gas−liquid mass transfer into account, expressed by a linear driving force model. It was chosen to write the governing equations as time differentials for mathematical convenience. The model converges from a set of initial conditions to the steady-state solutions. Only the latter have physical relevance and will be compared with the experimental data. 3.2. Material Balances. The hydrodynamic study confirmed that the reactor could be modeled by a CSTR.40 The mass balances over lump j in the liquid and the vapor phase can be written as follows:

Figure 3. Schematic drawing of the cold mock-up.

Hamilton Visiferm DO 120 probe. The time constant of the probe had been determined previously assuming a first-order dynamic. The water inlet reserve had been degassed in advance and was kept under a nitrogen atmosphere. Six experiments with varying volumetric flow rates have been performed (cf. Table 3).

3. MODEL DESCRIPTION 3.1. Model Assumptions. The five-lump kinetic model described by Nguyen et al.39 was adapted for the simulation of

dCjliq dt

(3)

Table 3. Experimental Volumetric Flow Rates Used for the Characterization of Gas−Liquid Mass Transfer Qv(liq) (mL/min)

Qv(gas) (mL/min)

0.58 0.58 0.37 0.31 0.28 0.22

5.90 5.90 3.75 3.21 2.81 2.24

V liq = Q vliq,inCjliq,in − Q vliqCjliq + rjV liq + Q n,exchange j

dCjvap dt

V liq = Q vvap,inCjvap,in − Q vvapCjvap − Q n,exchange j

(4)

The global mass balances over the liquid and vapor phases allow for the calculation of the liquid and vapor volumetric flow rates, respectively. For simplicity, we assumed ideal behavior for the gas phase. For the liquid phase, the densities at operating conditions were estimated by ProSimPlus. Total concentrations in gas and liquid phases are assumed to be constant. 15855



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Figure 4. Reaction network for AR conversion in the micropilot unit.

Q vliqρ liq = Q vliq,inρ liq,in − Q vvap ∑ CjvapMj

Q vvapP RT

=

Q vvap,inP RT

+ kLaV liq ∑ (C*j − Cjliq)

Table 4. Overview of Reaction Pathways, Stoichiometric and Kinetic Constants, and Activation Energies Used in the Micropilot Unit’s Model

(5)

ki (103 m3·mol−1·s−1)

(6)

The density of the inlet stream was estimated based on feedstock properties, while the density of the reaction mixture at the outlet was estimated based on hot separator bottom properties. 3.3. Kinetics. Kinetic parameters, such as rate constants and stoichiometric coefficients determined from batch reactor experiments,39 were used for the model of the continuous micropilot unit. The established reaction network is presented in Figure 4. The global volumetric production rate of lump j, rj (mol·m−3· −1 s ), in eq 3 is defined as the sum of the individual production rates of lump j in reaction i = 1, ..., 5 multiplied by the associated stoichiometric coefficient νij.

∑ νjikiCjliqC Hliq

2

i=1

reaction

420 °C

430 °C

1

RES + 5.84H2 → 1.6VGO + 0.62GAS RES + 3.49H2 → 2.67DIST + 0.99GAS VGO + 4.6H2 → 1.51DIST + 1.75GAS VGO + 2.08H2 → 2.8NAPH + 1.48GAS DIST + 4.07H2 → 1.72NAPH + 0.7GAS

5.53

12.0

25.4

313

21.5

42.4

284

10.7

207

2 3 4 5

10.6 3.90

6.51

0.658

1.25

12.0

19.5

2.33 31.3

260 196

by mass balance constraints. They were 610, 388, 218, 125, and 30 g/mol for lumps RES, VGO, DIST, NAPH, and GAS, respectively. For simplicity, they were kept constant for all simulations. 3.4. Hydrodynamics. Gas holdups, determined from cold mock-up experiments, were used for the model of the continuous micropilot unit.40 The volume of the liquid and vapor phases was calculated from the total reactor volume and the gas holdup ε.

5

rj =

EA 440 °C (kJ/mol)

i

(7)

Note that batch reactor experiments were performed at 420 and 430 °C. As the experiments in the micropilot unit were performed at 420, 430, and 440 °C, the kinetic constants were extrapolated to 440 °C with the Arrhenius law. However, k4(VGO→NAPH) had been determined to be negligible at 420 °C, while at 430 °C a value of 1250 m3·mol−1·s−1 had been estimated. Consequently, no activation energy had been determined that would enable us to estimate k4 at 440 °C. In the open literature, kinetic models similar to the one employed by Nguyen et al.39 rarely give an activation energy for the conversion of VGO to NAPH. This might be because of the rather small kinetic constant. In addition, activation energies can hardly be compared between different studies as most describe more or less apparent kinetics and not intrinsic kinetics. Loria et al. used a similar kinetic model for a similar process type.37 Similarly to Nguyen et al.,39 they found EA(VGO→DIST) = EA(DIST→NAPH). In addition, they found EA(VGO→NAPH) = 1.3EA(VGO→DIST). In the absence of a better estimate to determine the activation energy for the reaction VGO → NAPH for the kinetic mode of the micropilot unit, this ratio has been taken to calculate EA4 = 260 kJ/mol. This relatively high activation energy is in agreement with the fact that no significant kinetic constant was estimated for 420 °C. Stoichiometric and kinetic constants as well as activation energies used in the micropilot unit’s model are presented in Table 4. It is important to note that molar masses for each lump had also been derived from batch experiments. This was necessary as some of the stoichiometric coefficients had been determined

V liq = (1 − ε)V tot

(8)

V vap = εV tot

(9)

The following correlation between the gas holdup and the liquid and vapor volumetric flow rates had been established from cold mock-up experiments using a nontransferable tracer (NaCl).40 This predicts the experimental holdup values within an error margin of 15%. ⎛ ε (vol %) = 6.1567⎜Q vliq ⎝

⎛ cm 3 ⎞⎞ ⎟⎟ ⎜ ⎝ min ⎠⎠

0.4347 ⎛ ⎛ cm 3 ⎞⎞ ⎟ ⎜Q vvap ⎜ ⎟ ⎝ min ⎠⎠ ⎝

−0.3284

(10)

3.5. Thermodynamic Parameters. Mass transfers between liquid and vapor phases are expressed by a linear driving force model: Q n,exchange = kLa(C*j − Cjliq)V liq j

(11)

The equilibrium concentrations in the liquid phase, C*j , in eq 11 can be calculated from the molar flow rate of lump j in the liquid phase at thermodynamic equilibrium as follows: 15856



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Table 5. Inlet (Initial) Conditions of the Simulations run no. parameter vapor phase Qvvap,in Cvap,in(H2) liquid phase Qvliq,in Cliq,in(DIST) Cliq,in(VGO) Cliq,in(RES)

unit

1

2

3

4

5

6

10−9 m3·s−1 mol·m−3

96.5 2281

97.9 2248

99.3 2217

48.3 2281

48.9 2248

49.6 2217

10−9 m3·s−1 mol·m−3 mol·m−3 mol·m−3

11.0 208 866 677

11.1 207 861 673

11.2 205 856 669

5.51 208 866 677

5.53 207 861 673

5.60 205 856 669

Figure 5. Schematic drawing of the different liquid and vapor streams in the micropilot unit.

C*j =

Q n,*j,liq Q v*,liq

output to the experimental data. The MATLAB software package including the optimization toolbox has been used to solve the set of equations. The parameter estimation was done using the Levenberg−Marquardt algorithm, based on the comparison of the experimental and simulated data points (Xexp, Xsim) using the least-squares method and minimizing the difference Δ defined as

(12)

The flow rates at equilibrium conditions were determined by equilibrium flash calculations using ProSimPlus software. Thermodynamic properties were calculated using the Soave− Redlich−Kwong equation of state for the vapor phase and the Grayson−Streed model for the liquid phase. The API 6A2.22 method integrated in ProSimPlus was used for the calculation of the molar volume. 3.6. Volumetric Mass Transfer Coefficient. The volumetric mass transfer coefficient in eq 11 is defined as follows: kLa = kL

S exchange V liq

Δ=

dt

(13)

kLa′ − sN − k V11σ 2 < kLa < kLa′ + sN − k V11σ 2

(16)

where kLa′ is the estimation of kLa, V11 is the variance, and σ is the standard deviation. sN−k is the Student variable (corresponding to 95% probability confidence interval), where N is the observation number and k is the parameter number. The variance V11 = (STS)−1 is calculated by using the sensitivity S. The elements of S are defined as follows:

V liq = Q vliq,inCOliq,in − Q vliqCOliq2 2 + kLa(CO*2 − COliq2 )V liq

(15)

The precision of the estimated kLa values was determined using the following assumptions. The errors associated with two successive measurements were independent and centered and follow a normal distribution. The precision was calculated as follows:44

The kLa values had been determined from cold mock-up experiments using oxygen as a transferable tracer. The mass balance for the oxygen in the liquid phase can be written as follows: dCOliq2

∑ (X exp − X sim)2

(14)

3.7. Numerical Method. Parameter estimation methods allow the optimization of the kLa value by fitting the model

S= 15857

∂X ∂kLa

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4. RESULTS AND DISCUSSION The initial conditions of the model were those of the feedstock and hydrogen inlet. They are presented in Table 5. All other inlet concentrations are zero. Only the steady state has been compared with experimental data, which is reached after a time corresponding to about 4 times the residence time. 4.1. Optimization of kLa Values. In order to transpose the kinetics determined from a batch reactor to the micropilot unit model, the set of kinetic parameters and the thermodynamic description had to be kept the same. Preliminary simulations using kLa values obtained on the cold mock-up did not show satisfactory agreement between the pilot unit model and experimental results. Indeed, hydrodynamics and mass transfer characteristics had been determined with fluids, which gave a poor representation of the physical properties of the reaction mixture at operating conditions. Consequently, kLa values have been estimated for each run, keeping the correlation for the calculation of the gas holdup as determined on the cold mockup shown in eq 10. In order to compare the model’s output with the experimental results, it is important to note that the boundaries of the model do not correspond to those of the experiments as is illustrated in Figure 5. The samples are collected experimentally after the hot and cold separators corresponding to the exit of the system. The model contains only the stirred tank reactor and not the separation system. However, vapor−liquid mass transfer happens certainly in the hot separator. The hot separator model has not been developed, and therefore the simulated concentrations and volumetric flow rates at the exit of the system could not be obtained. The comparison between the model and experimental data has been performed with the total mass flow rates of each lump assuming that reactions do not take place in the hot separator. Figure 6 compares the yield of each lump for the conversion of 100 g of the feedstock as a function of the conversion of the RES (510 °C+) fraction. A very good agreement is obtained between the model and the experiment for yields of DIST, NAPH, and H2 lumps. Relative errors are smaller than 10% for H2 and vary from 5 to 20% for NAPH. DIST yields are in good agreement up to 40% RES conversion. However, at the highest conversions, the relative error between experimental and simulated yields is about 20%. VGO yields are systematically overestimated, especially at high conversions. As can be seen from Figure 6a, the experimental VGO yield decreases significantly for RES conversions higher than 50 wt %, while the simulated VGO yield remains practically constant. At the highest conversion, the relative error in VGO yield is about 20%. In fact, in the batch reactor study,39 the kinetic constants for VGO consumption have been obtained in the range of 0−40 wt % RES conversion. In this conversion range, the VGO yield is relatively stable. Therefore, the associated kinetic constants cannot allow good agreement for conversions higher than 40 wt %. Also, the underestimation of the GAS lump yields by 30− 45% can be explained by the observation that experimental gas yields were comparatively lower in the batch reactor than in the continuous micropilot unit. The optimized kLa values and associated uncertainty intervals as well as the standard deviation σ for each run are presented in Table 6. The model was found to be highly sensitive to variation of the mass transfer coefficient, which is consistent with the batch reactor study.39

Figure 6. Comparison between model output and experimental results. (a) Yield of liquid lumps as a function of RES (510 °C+) conversion. (b) Yield of gaseous lumps as a function of RES (510 °C +) conversion. Filled symbols, simulated data; empty symbols, experimental data.

In order to compare the optimized model’s output with the cold mock-up, the kLa values are shown as a function of the gas holdup in Figure 7. The error bars represent the precision as defined in eq 16. They indicate that the optimization is very sensitive to the kLa values for the cold mock-up study as well as for the model of the continuous pilot unit. It can be seen that the pair of values (ε, kLa) are close to those of the cold mock-up. The kLa normally depends on other properties such as viscosity, density, surface tension, etc.45−47 However, these results would suggest that the cold mock-up with a water−nitrogen/air system is able to determine the correct order of magnitude of the parameters that characterize hydrodynamics and mass transfer. 4.2. Mass Transfer in the Hot Separator. Having obtained a satisfying agreement between model and experiment by adjusting the mass transfer coefficient, the role of the hot separator can be studied further. Figure 8 compares the inlet and outlet streams of the hot separator. The model calculates the total volumetric flow rates as well as the composition of the 15858



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Table 6. Optimized kLa Values and Standard Deviations σ for Different Runs run no. kLa (10 σ

−3

−1

s )

1

2

3

4

5

6

0.965 ± 0.084 0.61

1.46 ± 0.12 2.29

1.58 ± 0.24 4.15

0.839 ± 0.044 1.27

1.10 ± 0.06 1.68

1.37 ± 0.01 15.30

Figure 7. Comparison of correlation between kLa and ε obtained on the cold mock-up (○) and from the optimized continuous pilot unit’s model (▲, run nos. 1−3; ◆, run nos. 4−6).

inlet streams of the hot separator. For the outlet stream, the same can be determined from experimental data. To this end, we assumed ideal behavior for the vapor phase (gas + cold separator bottom) and estimated the density of the liquid phase (hot separator bottom) at operating conditions of the hot separator with ProSimPlus. Figure 8a shows that the volumetric flow rates of the gas and the liquid at the outlet are not significantly different from those at the inlet. However, there is a change in the molar compositions of the gas and liquid phases. Parts b and c of Figure 8 compare the molar flow rates of the liquid phase and the gas phase, respectively, at the inlet and the outlet of the hot separator. The molar flow rate of RES does not vary significantly as it is not transferred between the phases. VGO molar flow rates of the liquid phase are slightly greater in the outlet stream than in the inlet stream. For the gas phase, the inverse is observed. This indicates that VGO is transferred from the gas phase to the liquid phase in the hot separator. This is consistent with the fact that the temperature in the CSTR is higher than that of the hot separator. The same tendency, but even more pronounced, is observed for the molar flow rates of DIST. Being lighter than VGO, a greater quantity of DIST was in the gas phase in the CSTR and is transferred to the liquid phase in the hot separator. NAPH, being even lighter, has less tendency to transfer into the liquid phase. These observations further illustrate that the hot separator is not capable of significantly increasing the RES concentration in the recycle stream, as was stated in our previous publication.40 For the lumps GAS and H2, the molar flow rates of the gas phase in the outlet stream are higher than in the inlet stream. These lumps are thus transferred from the liquid to the gas phase in the hot separator. For the GAS lump, this is difference is particularly pronounced due to the underestimation of the total gas yield (cf. also Figure 6b).

Figure 8. Comparison of hot separator inlet and outlet flows. (a) Volumetric flow rates. (b) Liquid phase molar flow rates. (c) Vapor phase molar flow rates.

residue has been proposed. The kinetic network as well as the thermodynamic model for the AR hydroconversion with dispersed catalysts had been obtained on a batch reactor. Hydrodynamics and mass transfer characteristics of the CSTR had been studied on a cold mock-up.

5. CONCLUSION A methodology for the development of a continuous microscale pilot unit model for slurry hydroconversion of a petroleum 15859



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The hydroconversion model of the continuous microscale pilot unit was found to be highly sensitive to the mass transfer coefficient. After optimization of the kLa values, a satisfactory agreement between simulations and the experimental data was obtained. Nevertheless, the kLa and ε values of the optimized model were consistent with those of the cold mock-up. This suggests that the cold mock-up, though being a very simplified representation of the real system, allows for the determination the correct order of magnitude of the kLa and ε values. Consequently, the chemical kinetics and thermodynamic model, as well as our methodology, were validated. This methodology seems to be a good approach to go from the batch reactor to the continuous pilot. However, we note that special attention must be paid to mass transfer and hydrodynamic parameters.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel.: (+33) 472445426. Present Addresses †

M.P.: TRTG, TOTAL Research & Technology Gonfreville, BP 27, F-76700 Harfleur, France. ‡ M.L.: TRTF, TOTAL Research & Technology Feluy, Zone Industrielle C, B-7181 Feluy, Belgium. Notes

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The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors acknowledge the financial and analytical support of Total Refining and Chemistry. Barbara Browning is acknowledged for her contribution to the manuscript.

R = ideal gas constant (J mol−1·K−1) RES = lump corresponding to the boiling point range of 510 °C+ rji = volumetric production rate of lump j in reaction i (mol· m−3·s−1) RTD = residence time distribution VGO = lump corresponding to the boiling point range of 180−350 °C Sexchange = exchange surface between liquid and vapor phases (m2) S = sensitivity sN−k = Student variable (corresponding to 95% probability confidence interval) T = temperature (K) V11 = variance V11= (STS)−1 Vliq = volume of liquid phase (m3) Vtot = total reactor volume without internals (m3) Vvap = volume of vapor phase (m3) Xexp = experimental data point Xsim = simulated data point Yj = yield of lump j (wt %) Δ = sum of the squares of the difference between experimental and simulated data points ε = gas holdup (vol %) ρliq = density of liquid phase (kg·m−3) σ = standard deviation νij = stoichiometric coefficient of lump j in reaction i

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ABBREVIATIONS AR = atmospheric residue Cjliq = molar concentration of lump j in liquid phase (mol· m−3) Cjvap = molar concentration of lump j in vapor phase (mol· m−3) C*j = molar concentration of lump j in the liquid phase in equilibrium with vapor phase (mol·m−3) CSB = cold separator bottom (liquid product) CSTR = continuous stirred tank reactor DIST = lump corresponding to the boiling point range of 180−350 °C EA = activation energy (kJ/mol) GAS = lump corresponding to all noncondensable gases except hydrogen HSB = hot separator bottom (liquid product) k = parameter number ki = kinetic constant of reaction i (m3·mol−1·s−1) kLa = volumetric mass transfer coefficient (s−1) kLa′ = estimation of volumetric mass transfer coefficient (s−1) Mj = molar mass of lump j (kg mol−1) N = observation number NAPH = lump corresponding to the boiling point range of 40−180 °C P = pressure (Pa) Qm = mass flow rate (kg·s−1) Qn = molar flow rate (mol·s−1) Qv = volumetric flow rate (m3·s−1) 15860



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Simulation of Petroleum Residue Hydroconversion in a Continuous

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