Kinetic Modelling Simulation and Optimal Operation of Trickle Bed Reactor for Hydrotreating of Crude Oil. Kinetic Parameters Estimation of Hydrotreating Reactions in Trickle Bed Reactor (TBR) via Pilot Plant Experiments; Optimal Design and Operation of an Industrial TBR with Heat Integration and Economic Evaluation.

Catalytic hydrotreating (HDT) is a mature process technology practiced in the petroleum refining industries to treat oil fractions for the removal of impurities (such as sulfur, nitrogen, metals, asphaltene). Hydrotreating of whole crude oil is a new technology and is regarded as one of the more difficult tasks that have not been reported widely in the literature. In order to obtain useful models for the HDT process that can be confidently applied to reactor design, operation and control, the accurate estimation of kinetic parameters of the relevant reaction scheme are required. This thesis aims to develop a crude oil hydrotreating process (based on hydrotreating of whole crude oil followed by distillation) with high efficiency, selectivity and minimum energy consumption via pilot plant experiments, mathematical modelling and optimization. To estimate the kinetic parameters and to validate the kinetic models under different operating conditions, a set of experiments were carried out in a continuous flow isothermal trickle bed reactor using crude oil as a feedstock and commercial cobaltmolybdenum on alumina (Co-Mo/¿-Al2O3) as a catalyst. The reactor temperature was varied from 335°C to 400°C, the hydrogen pressure from 4 to10 MPa and the liquid hourly space velocity (LHSV) from 0.5 to 1.5 hr-1, keeping constant hydrogen to oil ratio (H2/Oil) at 250 L/L. The main hydrotreating reactions were hydrodesulfurization (HDS), hydrodenitrogenation (HDN), hydrodeasphaltenization (HDAs) and hydrodemetallization (HDM) that includes hydrodevanadization (HDV) and hydrodenickelation (HDNi). An optimization technique is used to evaluate the best kinetic models of a trickle-bed reactor (TBR) process utilized for HDS, HDAs, HDN, HDV and HDNi of crude oil based on pilot plant experiments. The minimization of the sum of the squared errors (SSE) between the experimental and estimated concentrations of sulfur (S), nitrogen (N), asphaltene (Asph), vanadium (V) and nickel (Ni) compounds in the products, is used as an objective function in the optimization problem using two approaches (linear (LN) and non-linear (NLN) regression). The growing demand for high-quality middle distillates is increasing worldwide whereas the demand for low-value oil products, such as heavy oils and residues, is decreasing. Thus, maximizing the production of more liquid distillates of very high quality is of immediate interest to refiners. At the same time, environmental legislation has led to more strict specifications of petroleum derivatives. Crude oil hydrotreatment enhances the productivity of distillate fractions due to chemical reactions. The hydrotreated crude oil was distilled into the following fractions (using distillation pilot plant unit): light naphtha (L.N), heavy naphtha (H.N), heavy kerosene (H.K), light gas oil (L.G.O) and reduced crude residue (R.C.R) in order to compare the yield of these fractions produced by distillation after the HDT process with those produced by conventional methods (i.e. HDT of each fraction separately after the distillation). The yield of middle distillate showed greater yield compared to the middle distillate produced by conventional methods in addition to improve the properties of R.C.R. Kinetic models that enhance oil distillates productivity are also proposed based on the experimental data obtained in a pilot plant at different operation conditions using the discrete kinetic lumping approach. The kinetic models of crude oil hydrotreating are assumed to include five lumps: gases (G), naphtha (N), heavy kerosene (H.K), light gas oil (L.G.O) and reduced crude residue (R.C.R). For all experiments, the sum of the squared errors (SSE) between the experimental product compositions and predicted values of compositions is minimized using optimization technique. The kinetic models developed are then used to describe and analyse the behaviour of an industrial trickle bed reactor (TBR) used for crude oil hydrotreating with the optimal quench system based on experiments in order to evaluate the viability of large-scale processing of crude oil hydrotreating. The optimal distribution of the catalyst bed (in terms of optimal reactor length to diameter) with the best quench position and quench rate are investigated, based upon the total annual cost. The energy consumption is very important for reducing environmental impact and maximizing the profitability of operation. Since high temperatures are employed in hydrotreating (HDT) processes, hot effluents can be used to heat other cold process streams. It is noticed that the energy consumption and recovery issues may be ignored for pilot plant experiments while these energies could not be ignored for large scale operations. Here, the heat integration of the HDT process during hydrotreating of crude oil in trickle bed reactor is addressed in order to recover most of the external energy. Experimental information obtained from a pilot scale, kinetics and reactor modelling tools, and commercial process data, are employed for the heat integration process model. The optimization problem is formulated to optimize some of the design and operating parameters of integrated process, and minimizing the overall annual cost is used as an objective function. The economic analysis of the continuous whole industrial refining process that involves the developed hydrotreating (integrated hydrotreating process) unit with the other complementary units (until the units that used to produce middle distillate fractions) is also presented. In all cases considered in this study, the gPROMS (general PROcess Modelling System) package has been used for modelling, simulation and parameter estimation via optimization process.Tikrit University, Ira

Optimal design and operation of an industrial fluidized catalytic cracking reactor

YesFluidized catalytic cracking (FCC) is regarded one of the most significant operations in the oil refining industries to convert feedstock (mainly vacuum gasoil) to valuable products (namely gasoline and diesel). The behavior of the fluidized catalytic cracking process is playing a main part on the overall benefits of refinery units and improving in process or control of fluidized catalytic cracking plants will result in exciting benefits economically. According to these highlights, this study is aimed to develop a new mathematical model for the FCC process taking into account the complex hydrodynamics of the reactor regenerator system with a new six lumps kinetic model for the riser. The mathematical model, simulation and optimization have done utilizing vacuum gas oil (VGO) as a feedstock and zeolite as a catalyst under the following operating conditions: temperature (733K, 783K, and 813K), weight hourly space velocity (5, 20 and 30hr−1) and catalyst to oil ratio (4, 7 and 10). The best kinetic parameters of the relevant reactions are estimated using the optimization technique based on the experimental results taken from literature. The effect of operating condition (mainly, reaction temp (T), catalyst to oil ratio (CTO) and weight hourly space velocity (WHSV) on the product composition has also been discussed. The optimal kinetic parameters obtained from the pilot plant scale have been employed to develop an industrial FCC process, where optimal operating condition based on maximum conversion of VGO with minimum cost in addition to maximizing the octane number of gasoline (GLN), have been studied. Minimum coke content deposition the catalyst within the regenerator is also investigated here. New results (the highest conversion and octane number, and the lowest coke content) have obtained in comparison with those reported in the literature

Optimal Design and Operation of an Industrial Three Phase Reactor for the Oxidation of Phenol

YesAmong several treatment methods Catalytic Wet Air Oxidation (CWAO) treatment is considered as a useful and powerful method for removing phenol from waste waters. In this work, mathematical model of a trickle bed reactor (TBR) undergoing CWAO of phenol is developed and the best kinetic parameters of the relevant reaction are estimated based on experimental data (from the literature) using parameter estimation technique. The validated model is then utilized for further simulation and optimization of the process. Finally, the TBR is scaled up to predict the behavior of CWAO of phenol in industrial reactors. The optimal operating conditions based on maximum conversion and minimum cost in addition to the optimal distribution of the catalyst bed is considered in scaling up and the optimal ratio of the reactor length to reactor diameter is calculated with taking into account the hydrodynamic factors (radial and axial concentration and temperature distribution)

Design of a Synthetic Zinc Oxide Catalyst over Nano-Alumina for Sulfur Removal by Air in a Batch Reactor

Owing to the environmental regulations with respect to sulfur content and continuing challenges of finding a suitable catalyst of such impurity, a driving force for the development of more efficient technologies a deep research on new oxidative catalysts is considered an important issue in fuel quality improvement. Thus, the present study shows a novel percent of nano-catalyst with 18% zinc oxide (ZnO) of active component over nano-alumina that has not been reported in the public domain for sulfur removal from kerosene fuel by air (oxidative desulfurization (ODS) method). Where, such percent of the active component on the nano-alumina helps to add one or two atoms of oxygen to sulfur content in the kerosene. The nano-catalyst (ZnO/nano-alumina-particles composite) is prepared by precipitation of zinc oxide and loaded over nano-alumina in one-step. The activity of the prepared catalyst was tested utilizing ODS process of kerosene fuel by air in a batch reactor. A set of experiments were conducted with a wide range of operating conditions, where the reaction temperature was ranged from 150 to 190ºC, the reaction time from 30 to 50 min and the catalyst weight from 0.4 to 1 g. The experimental results showed that the chemical nature of zinc oxides showed higher conversion (70.52%) at reaction temperature of 190 ºC, reaction time of 50 min, and 1 g catalyst weight used in the batch reactor. A kinetic model related to the sulfur removal from kerosene via ODS process in the batch reactor was also investigated in this study for the purpose of estimating the best kinetic parameters of the relevant reactions. The results showed that the prepared catalyst (ZnO over nano-alumina) can be applied confidently to reactor design, operation and control in addition to improve the fuel quality. Following the kinetic model of ODS process, a very well agreement between the experimental and predicted results is obtained. Copyright © 2019 BCREC Group. All rights reserve

Significant cost and energy savings opportunities in industrial three phase reactor for phenol oxidation

YesEnergy saving is an important consideration in process design for low cost sustainable production with reduced environmental impacts (carbon footprint). In our earlier laboratory scale pilot plant study of catalytic wet air oxidation (CWAO) of phenol (a typical compound found in wastewater), the energy recovery was not an issue due to small amount of energy usage. However, this cannot be ignored for a large scale reactor operating around 140–160 °C due to high total energy requirement. In this work, energy savings in a large scale CWAO process is explored. The hot and cold streams of the process are paired up using 3 heat exchangers recovering significant amount of energy from the hot streams to be re-used in the process leading to over 40% less external energy consumption. In addition, overall cost (capital and operating) savings of the proposed process is more than 20% compared to that without energy recovery option

Improvement of fuel quality by oxidative desulfurization: Design of synthetic catalyst for the process

YesThe present study explored a novel oxidative desulfurization (ODS) method of light gas oil fuel, which combines a catalytic oxidation step of the dibenzothiophene compound directly in the presence of molecular air as oxidant to obtain high quality fuel for light gas oil. In chemical industries and industrial research, catalysis play a significant role. Heightened concerns for cleaner air together with stricter environmental legislations on sulphur content in addition to fulfill economic have created a driving force for the improvement of more efficient technologies and motivating an intensive research on new oxidative catalysts. As the lower quality fuel becomes more abundant, additional challenges arise such as more severe operation conditions leading to higher corrosion of the refinery installations, catalyst deactivation and poisoning. Therefore, among the technologies to face these challenges is to develop catalysts that can be applied economically under moderate conditions. The objective of this work is to design a suitable synthetic catalyst for oxidative desulfurization (ODS) of light gas oil (LGO) containing model sulphur compound (dibenzothiophene (DBT)) using air as oxidant and operating under different but moderate operating conditions. The impregnation method is used to characterize two homemade catalysts, cobalt oxide (Co3O4/γ-Al2O3) and manganese oxide (MnO2/γ-Al2O3). The prepared catalysts showed that the manganese oxide has a good impregnation (MnO2=13%), good pore size distribution and larger surface area. A set of experiments related to ODS of dibenzothiophene has been carried out in a continuous flow isothermal trickle bed reactor using light gas oil as a feedstock utilizing both catalysts prepared in-house. At constant pressure of 2 bar and with different initial concentration of sulphur within dibenzothiophene, the temperature of the process was varied from 403K to 473K and the liquid hourly space velocity from(LHSV) was varied from 1 to 3 hr-1. The results showed that an increase in reaction temperature and decreasing in LHSV, higher conversion was obtained. Although both catalysts showed excellent catalytic performance on the removal of molecule sulphur compound from light gas oil, the catalyst MnO2 catalyst exhibited higher conversion than Co3O4 catalyst at the same process operating conditions

Kinetic modelling simulation and optimal operation of trickle bed reactor for hydrotreating of crude oil : kinetic parameters estimation of hydrotreating reactions in trickle Bbed reactor (TBR) via pilot plant experiments : optimal design and operation of an industrial TBR with heat integration and economic evaluation

Catalytic hydrotreating (HDT) is a mature process technology practiced in the petroleum refining industries to treat oil fractions for the removal of impurities (such as sulfur, nitrogen, metals, asphaltene). Hydrotreating of whole crude oil is a new technology and is regarded as one of the more difficult tasks that have not been reported widely in the literature. In order to obtain useful models for the HDT process that can be confidently applied to reactor design, operation and control, the accurate estimation of kinetic parameters of the relevant reaction scheme are required. This thesis aims to develop a crude oil hydrotreating process (based on hydrotreating of whole crude oil followed by distillation) with high efficiency, selectivity and minimum energy consumption via pilot plant experiments, mathematical modelling and optimization. To estimate the kinetic parameters and to validate the kinetic models under different operating conditions, a set of experiments were carried out in a continuous flow isothermal trickle bed reactor using crude oil as a feedstock and commercial cobaltmolybdenum on alumina (Co-Mo/γ-Al2O3) as a catalyst. The reactor temperature was varied from 335°C to 400°C, the hydrogen pressure from 4 to10 MPa and the liquid hourly space velocity (LHSV) from 0.5 to 1.5 hr-1, keeping constant hydrogen to oil ratio (H2/Oil) at 250 L/L. The main hydrotreating reactions were hydrodesulfurization (HDS), hydrodenitrogenation (HDN), hydrodeasphaltenization (HDAs) and hydrodemetallization (HDM) that includes hydrodevanadization (HDV) and hydrodenickelation (HDNi). An optimization technique is used to evaluate the best kinetic models of a trickle-bed reactor (TBR) process utilized for HDS, HDAs, HDN, HDV and HDNi of crude oil based on pilot plant experiments. The minimization of the sum of the squared errors (SSE) between the experimental and estimated concentrations of sulfur (S), nitrogen (N), asphaltene (Asph), vanadium (V) and nickel (Ni) compounds in the products, is used as an objective function in the optimization problem using two approaches (linear (LN) and non-linear (NLN) regression). The growing demand for high-quality middle distillates is increasing worldwide whereas the demand for low-value oil products, such as heavy oils and residues, is decreasing. Thus, maximizing the production of more liquid distillates of very high quality is of immediate interest to refiners. At the same time, environmental legislation has led to more strict specifications of petroleum derivatives. Crude oil hydrotreatment enhances the productivity of distillate fractions due to chemical reactions. The hydrotreated crude oil was distilled into the following fractions (using distillation pilot plant unit): light naphtha (L.N), heavy naphtha (H.N), heavy kerosene (H.K), light gas oil (L.G.O) and reduced crude residue (R.C.R) in order to compare the yield of these fractions produced by distillation after the HDT process with those produced by conventional methods (i.e. HDT of each fraction separately after the distillation). The yield of middle distillate showed greater yield compared to the middle distillate produced by conventional methods in addition to improve the properties of R.C.R. Kinetic models that enhance oil distillates productivity are also proposed based on the experimental data obtained in a pilot plant at different operation conditions using the discrete kinetic lumping approach. The kinetic models of crude oil hydrotreating are assumed to include five lumps: gases (G), naphtha (N), heavy kerosene (H.K), light gas oil (L.G.O) and reduced crude residue (R.C.R). For all experiments, the sum of the squared errors (SSE) between the experimental product compositions and predicted values of compositions is minimized using optimization technique. The kinetic models developed are then used to describe and analyse the behaviour of an industrial trickle bed reactor (TBR) used for crude oil hydrotreating with the optimal quench system based on experiments in order to evaluate the viability of large-scale processing of crude oil hydrotreating. The optimal distribution of the catalyst bed (in terms of optimal reactor length to diameter) with the best quench position and quench rate are investigated, based upon the total annual cost. The energy consumption is very important for reducing environmental impact and maximizing the profitability of operation. Since high temperatures are employed in hydrotreating (HDT) processes, hot effluents can be used to heat other cold process streams. It is noticed that the energy consumption and recovery issues may be ignored for pilot plant experiments while these energies could not be ignored for large scale operations. Here, the heat integration of the HDT process during hydrotreating of crude oil in trickle bed reactor is addressed in order to recover most of the external energy. Experimental information obtained from a pilot scale, kinetics and reactor modelling tools, and commercial process data, are employed for the heat integration process model. The optimization problem is formulated to optimize some of the design and operating parameters of integrated process, and minimizing the overall annual cost is used as an objective function. The economic analysis of the continuous whole industrial refining process that involves the developed hydrotreating (integrated hydrotreating process) unit with the other complementary units (until the units that used to produce middle distillate fractions) is also presented. In all cases considered in this study, the gPROMS (general PROcess Modelling System) package has been used for modelling, simulation and parameter estimation via optimization process.EThOS - Electronic Theses Online ServiceTikrit University, IraqGBUnited Kingdo

Improvement of the middle distillate yields during crude oil hydrotreatment in a trickle-bed reactor

The growing demand for high-quality middle distillates is increasing worldwide, whereas the demand for low-value oil products, such as heavy oils and residues, is decreasing. Thus, maximizing the production of more liquid distillates of very high quality is of immediate interest to refiners. At the same time, environmental legislation has led to more strict specifications of petroleum derivatives. Hydrotreatment (HDT) of crude oil is one of the most challenging tasks in the petroleum refining industry, which has not been reported widely in the literature. In this work, crude oil was hydrotreated upon a commercial cobalt¿molybdenum on alumina (Co¿Mo/¿-Al2O3) catalyst presulfided at specified conditions. Detailed pilot-plant experiments were conducted in a continuous-flow isothermal trickle-bed reactor (TBR), and the main hydrotreating reactions were hydrodesulfurization (HDS), hydrodenitrogenation (HDN), hydrodeasphaltenization (HDAs), and hydrodemetallization (HDM), which includes hydrodevanadization (HDV) and hydrodenickelation (HDNi). The reaction temperature (T), the hydrogen pressure (P), and the liquid hourly space velocity (LHSV) were varied with certain ranges, with constant hydrogen to oil (H2/Oil) ratio. The effects of T, P, and LHSV on the conversion of sulfur, nitrogen, vanadium, nickel, and asphaltene were studied. The results showed that high T and P and low LHSV in HDS, HDN, HDV, HDNi, and HDAs of crude oil improve the sulfur (S), nitrogen (N), metals [vanadium (V) and nickel (Ni)], and asphaltene (Asph) conversion. The hydrotreated crude oil has been distilled into the following fractions: light naphtha (LN), heavy naphtha (HN), heavy kerosene (HK), light gas oil (LGO), and reduced crude residue (RCR), to compare the yield of these fractions produced by distillation after the HDT process to those produced by conventional methods (i.e., HDT of each fraction separately after the distillation). The yield of the middle distillate showed greater yield compared to the middle distillate produced by conventional methods. The properties of RCR produced using both methods are also discussed

Improving fuel quality by whole crude oil hydrotreating: A kinetic model for hydrodeasphaltenization in a trickle bed reactor

Fossil fuel is still a predominant source of the global energy requirement. Hydrotreating of whole crude oil has the ability to increase the productivity of middle distillate fractions and improve the fuel quality by simultaneously reducing contaminants such as sulfur, nitrogen, vanadium, nickel and asphaltene to the levels required by the regulatory bodies. Hydrotreating is usually carried out in a trickle bed reactor (TBR) where hydrodesulfurization (HDS), hydrodenitrogenation (HDN), hydrodemetallization (HDM) and hydrodeasphaltenization (HDAs) reactions take place simultaneously. To develop a detailed and a validated TBR process model which can be used for design and optimization of the hydrotreating process, it is essential to develop kinetic models for each of these reactions. Most recently, the authors have developed kinetic models for all of these chemical reactions except that of HDAs. In this work, a kinetic model (in terms of kinetic parameters) for the HDAs reaction in the TBR is developed. A three phase TBR process model incorporating the HDAs reactions with unknown kinetic parameters is developed. Also, a series of experiments has been conducted in an isothermal TBR under different operating conditions affecting the removal of asphaltene. The unknown kinetic parameters are then obtained by applying a parameter estimation technique based on minimization of the sum of square errors (SSEs) between the experimental and predicted concentrations of asphaltene compound in the crude oil. The full model with the estimated kinetic parameters is then applied to evaluate the removal of asphaltene (thus affecting fuel quality) under different operating conditions (than those used in experiments)