New catalyst development for the hydrotreating process, employing functionalized mesoporous carbon (mC) support is studied. mC support was prepared by the volume templating of alkali modified SBA-15 using sucrose as the carbon source and then functionalized using nitric acid of various concentrations (upto 8M HNO3). A series of NiMo catalysts (12% Mo and 2.4% Ni) were prepared using these functionalized mC supports. The supports and catalysts were characterized by N2 physisorption, SAXS, XRD, FTIR, TGA, SEM, TEM, H2-TPR and HRTEM. SAXS results indicated mild reduction in ordered structure of mesoporous carbons after functionalization. N2 physisorption analysis indicated progressive reduction in surface area and pore volume with the increase in nitric acid concentration. Enhancement of surface functional groups and acidity after functionalization were observed through FTIR spectroscopy and Boehm titration. SEM images showed the retention of needle like morphology in all functionalized carbon supports. TEM images showed that the increase in nitric acid concentration causes excessive etching, resulting in the reduction of ordered structure of functionalized mesoporous carbons. Hydrotreating study of these NiMo/mC catalysts were carried out under industrial operating conditions in a laboratory scale trickle bed reactor using coker light gas oil derived from Athabasca bitumen as feedstock. NiMo catalyst supported on 6M acid treated mC (i.e. NiMo/mC-6M) showed the highest activity due to higher surface functional groups, higher acidity and better textural properties. The HDS and HDN activities of NiMo/mC-6M catalyst were higher than that of NiMo/ã-Al2O3 catalyst owing to lower support metal interaction (SMI), higher surface area and effective functionalization. Using the mC-6M support, NiMo catalysts with different metal loading (12 27% Mo, 2.4 to 5.4% Ni) were prepared and characterized. Hydrotreating activity study of these catalysts indicated that the catalyst with 22% Mo and 2.9% Ni loading was the optimum catalyst on 6M functionalized mC support. Higher metal loading (>22%Mo) led to excessive pore blockage and improper metal dispersion resulting in decreased activity. Kinetic study of the optimum catalyst was carried out by varying temperature (330°C to 370°C), gas-to-oil ratio (400 1000 Nm3/m3), LHSV (1.0 to 2.5 hr-1) and pressure (7.8 to 9.8 MPa) and the data was fitted by non-linear regression method using power law model. The calculated reaction orders and activation energies were 2.8, 1.5 and 189 KJ/mol, 98.9 KJ/mol for HDS and HDN, respectively. The results of HRTEM and H2-TPR indicated lower SMI in mC supported catalyst resulting in the generation of qualitatively Type-II like NiMoS phase on functionalized mC supports, which is considered to be very active for hydrotreating. The hydrotreating activity of the optimum catalyst was higher than that of commercial catalyst (supported on ã-Al2O3). Long term deactivation experiment carried out over a total period of 10 weeks confirmed the durability of NiMo/mC catalyst for the duration of operation. This study reveals the immense capability of functionalized mC supports to become the potential alternative catalyst support to conventional ã-Al2O3 for the hydrotreating of gas oil feedstocks.

Neste trabalho é abordado o problema de controle e de otimização de unidades industriais de hidrotratamento de diesel (UHDT) por controladores MPC (Model Predictive Control). É apresentado um breve histórico dos controladores MPC convencionais e de horizonte infinito (IHMPC), bem como uma breve descrição do processo de Hidrotratamento de Diesel e das particularidades da aplicação do controle de processos a este tipo de planta industrial. Em seguida foi gerado, passo a passo, um algoritmo de controle que sumarizou e agregou características de vários controladores MPC disponíveis na literatura aberta, em especial os que foram desenvolvidos ao longo dos últimos anos pelo laboratório de simulação e controle da USP (LSCP), a fim de se obter um algoritmo adequado para a solução do problema de controle abordado. Em ambiente computacional de simulação, o algoritmo resultante possibilitou controlar e otimizar simultaneamente processos contínuos, sendo capaz de estabilizar a planta industrial de forma robusta e, ao mesmo tempo, aumentar a lucratividade de sua operação. Para tanto, foi desenvolvida uma função objetivo econômica que aumentou a conversão da carga bruta em produtos hidrotratados e minimizou o consumo de insumos, sendo que essa correlação foi agregada ao algoritmo de controle. As simulações permitiram que as estratégias de controle previamente discutidas pudessem ser testadas e seus resultados apresentados e debatidos. / This work addresses the control and optimization problem of industrial diesel hydrotreating units (UHDT) by MPC controllers (Model Predictive Control). It is presented a brief historical of conventional MPC controllers and infinite horizon controllers (IHMPC), as well as a brief description of the Diesel Hydrotreating process and the particulars of the application of process control for this type of industrial plant. It was then generated, step by step, one algorithm that summarized and aggregated control characteristics of various MPC controllers available in the open literature, in particular those that have been developed over the past few years by USPs laboratory of simulation and control of (LSCP), in order to obtain an algorithm suitable for solving the addressed control problem. In a computational simulation environment, the resulting algorithm allowed to simultaneously control and optimize continuous processes, being able to robustly stabilize the industrial plant and at the same time increase the profitability of its operation. For this purpose, an \"objective function\" was developed which increased the economic conversion of crude feed to hydrotreated product and minimized the consumption of raw materials, and this correlation was added to the control algorithm. The simulations allowed that the previously discussed control strategies could be tested and the results presented and discussed.

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.

PetrÃleo Brasileiro S/A / O objetivo principal à determinar a atividade catalÃtica residual e as causas da desativaÃÃo de amostras de catalisadores de uma unidade de HDT de lubrificantes. Foram realizadas corridas em unidade piloto, caracterizaÃÃo dos catalisadores e coletados dados do histÃrico operacional da unidade industrial. A atividade catalÃtica foi determinada atravÃs das conversÃes das reaÃÃes de HDA, HDS e HDN bem como pelos parÃmetros cinÃticos aparentes de um modelo de lei das potÃncias e lei de Arrhenius. Os catalisadores dos leitos principais de entrada e saÃda dos reatores industrial foram os mais desativados e o menos desativado o do leito intermediÃrio sendo estabelecida a seguinte ordem de atividade catalÃtica residual: R1L3 (meio) > R1L2 (topo)  R2L2 (fundo). Os resultados de teor e caracterÃsticas do coque, contaminantes e propriedades texturais sugerem que mecanismos distintos tenham causado a desativaÃÃo desses catalisadores: deposiÃÃo de metais e deposiÃÃo de coque. Os mecanismos de desativaÃÃo foram fortemente influenciados pelo posicionamento das amostras no interior do leito catalÃtico. No inÃcio do leito, a contaminaÃÃo por metais (notadamente Si e As) revelou-se o principal mecanismo de desativaÃÃo. Jà no final do leito, a deposiÃÃo de coque foi o mecanismo preponderante e a temperatura de reaÃÃo identificada como a principal causa para o maior envelhecimento do coque. / The main objective of this work is to study the residual catalyst activity and the mechanisms of deactivation of catalyst from a lube-oil hydroprocessing industrial unit. In order to accomplish this, pilot plant tests were carried out followed by spent catalysts characterization. The residual catalytic activity was determined by HDA, HDS and HDN conversions and adjusted by a power law apparent kinetic model. Pilot plant tests revealed different levels of residual activity for spent catalyst samples. Catalyst samples taken from the first and last of the five catalytic beds showed higher deactivation than others. Catalyst characterization results pointed out two mechanisms as the main reason for the catalytic deactivation through the industrial reactor: poisoning by metal deposition (mainly Si and As) and coke deposition. Poisoning was the main deactivation mechanism for the first bed spent catalyst sample, while coke deposition was predominant at the last catalytic bed sample. Reactor temperature was identified as the most important operational parameter considering coke aging.

This thesis summarizes the methods and major findings of Ni-W(P)/ã-Al2O3 nitride cata-lyst synthesis, characterization, hydrotreating activity, kinetic analysis and correlation of the catalysts activities to their synthesis parameters and properties.<p> The range of parameters for catalyst synthesis were W (15-40 wt%), Ni (0-8 wt%), P (0-5 wt%) and nitriding temperature (TN) (500-900 °C). Characterization techniques used included: N2 sorption studies, chemisorption, elemental analysis, temperature programmed studies, x-ray diffraction, scanning electron microscopy, energy dispersive x-ray, infrared spectroscopy, trans-mission electron microscopy and x-ray absorption near edge structure. Hydrodesulfurization (HDS), hydrodenitrogenation (HDN) and hydrodearomatization (HDA) were performed at: tem-perature (340-380 °C), pressure (6.2-9.0 MPa), liquid hourly space velocity (1-3 h-1) and hydro-gen to oil ratio (600 ml/ml, STP).<p> The predominant species on the catalyst surface were Ni3N, W2N and bimetallic Ni2W3N. The bimetallic Ni-W nitride species was more active than the individual activities of the Ni3N and W2N. P increased weak acid sites while nitriding temperature decreased amount of strong acid sites. Low nitriding temperature enhanced dispersion of metal particles. P interacted with Al2O3 which increased the dispersion of metal nitrides on the catalyst surface. HDN activity in-creased with Ni and P loading but decreased with increase in nitriding temperature (optimum conversion; 60 wt%). HDS and HDA activities went through a maximum with increase in the synthesis parameters (optimum conversions; 88. wt% for HDS and 47 wt% for HDA). Increase in W loading led to increase in catalyst activity. The catalysts were stable to deactivation and had the nitride structure conserved during hydrotreating in the presence of hydrogen sulfide.<p> The results showed good correlation between hydrotreating activities (HDS and HDN) and the catalyst nitrogen content, number of exposed active sites, catalyst particle size and BET surface area.<p> HDS and HDN kinetic analyses, using Langmuir-Hinshelwood models, gave activation energies of 66 and 32 kJ/mol, respectively. There were no diffusion limitations in the reaction process. Two active sites were involved in HDS reaction while one site was used for HDN. HDS and HDN activities of the Ni-W(P)/ã-Al2O3 nitride catalysts were comparable to the corre-sponding sulfides.

This thesis summarizes the methods and major findings of Ni-W(P)/ã-Al2O3 nitride cata-lyst synthesis, characterization, hydrotreating activity, kinetic analysis and correlation of the catalysts activities to their synthesis parameters and properties.<p> The range of parameters for catalyst synthesis were W (15-40 wt%), Ni (0-8 wt%), P (0-5 wt%) and nitriding temperature (TN) (500-900 °C). Characterization techniques used included: N2 sorption studies, chemisorption, elemental analysis, temperature programmed studies, x-ray diffraction, scanning electron microscopy, energy dispersive x-ray, infrared spectroscopy, trans-mission electron microscopy and x-ray absorption near edge structure. Hydrodesulfurization (HDS), hydrodenitrogenation (HDN) and hydrodearomatization (HDA) were performed at: tem-perature (340-380 °C), pressure (6.2-9.0 MPa), liquid hourly space velocity (1-3 h-1) and hydro-gen to oil ratio (600 ml/ml, STP).<p> The predominant species on the catalyst surface were Ni3N, W2N and bimetallic Ni2W3N. The bimetallic Ni-W nitride species was more active than the individual activities of the Ni3N and W2N. P increased weak acid sites while nitriding temperature decreased amount of strong acid sites. Low nitriding temperature enhanced dispersion of metal particles. P interacted with Al2O3 which increased the dispersion of metal nitrides on the catalyst surface. HDN activity in-creased with Ni and P loading but decreased with increase in nitriding temperature (optimum conversion; 60 wt%). HDS and HDA activities went through a maximum with increase in the synthesis parameters (optimum conversions; 88. wt% for HDS and 47 wt% for HDA). Increase in W loading led to increase in catalyst activity. The catalysts were stable to deactivation and had the nitride structure conserved during hydrotreating in the presence of hydrogen sulfide.<p> The results showed good correlation between hydrotreating activities (HDS and HDN) and the catalyst nitrogen content, number of exposed active sites, catalyst particle size and BET surface area.<p> HDS and HDN kinetic analyses, using Langmuir-Hinshelwood models, gave activation energies of 66 and 32 kJ/mol, respectively. There were no diffusion limitations in the reaction process. Two active sites were involved in HDS reaction while one site was used for HDN. HDS and HDN activities of the Ni-W(P)/ã-Al2O3 nitride catalysts were comparable to the corre-sponding sulfides.

Diesel plays an important role to the Brazil’s energy matrix, because it is one of the most consumed fuel at country. This study describes the hydrotreating process for petroleum refining using commercial software, PRO/II®. In addition, the artificial neural networks (ANN), using MATLAB®, were evaluated as tool for the development of virtual sensors and fault detection in chemical processes. The theoretical and practical assessment carried out in relation to the suitability of the software is justified by having acceptability in the oil and gas industry. For the oil hydrotreating associated with sulfur, the Diesel was represented by weight oil features; similar those used in refinery Abreu e Lima (RNEST). The goal of this study was to modeling in stationary condition for the reactor section the diesel hydrotreating process getting operating conditions to keep the sulfur concentration below of the ANP (Agência Nacional do Petróleo) specification, which is 10 ppm. The RNA applied to evaluate the virtual sensors was the MLP (Multi-Layer Perceptron), however, using the Levenberg-Marquardt Backpropagation (LMB) training algorithm. The coefficient of correlation was close to 1, so it means the network was satisfactory for this study. In the binary classification stage, the performance of RNA-LMB was efficient since a percentage of success above 93% was observed. In data clustering stage, used to define faults detection from parameters like flow of diesel, contaminants, pressure and temperature, the RNA-Kohonen was evaluated to check the sensitivity of the network to cluster the data with similarity. In a second stage, were inserted errors in the network, the temperature was the parameter with the greatest susceptibility to measurement errors in the industry. The lack of similarity for the input data in the RNA was well represented by self-organizing map (SOM). The simulations, as well as network training, adequately represent the analyzed processes. / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / O presente trabalho aborda o estudo do processo de hidrotratamento no refino de petróleo utilizando e avaliando software comercial, PRO/II®, e investiga a utilização da aplicação das redes neurais artificiais (RNA), em ambiente Matlab®, como ferramenta para o desenvolvimento de sensores virtuais e detecção de falhas em processos químicos. A avaliação teórica e prática realizada em relação à adequabilidade do software são justificadas pela sua aceitabilidade na área de petróleo e gás. Para a representação do diesel, combustível de maior interesse por ser o mais consumido dentro da matriz energética brasileira, foram utilizados dados associados ao petróleo pesado, obtidos da literatura, com características semelhantes ao que será utilizado na refinaria Abreu e Lima (RNEST). Petróleos com maiores índices de contaminantes como enxofre e nitrogênio estão cada vez mais presentes nas cargas das unidades de refino o que aumenta o interesse nos estudos referentes ao hidrotratamento (HDT). A principal variável estudada neste trabalho foi a avaliação da remoção do enxofre via HDT. O trabalho propôs uma modelagem estacionária da seção de reatores do processo de hidrotratamento de diesel obtendo condições operacionais que possibilite a manutenção do teor de enxofre abaixo da concentração de especificação da ANP, 10 ppm de enxofre no diesel. A RNA utilizada para a avaliação dos sensores virtuais foi a MLP (Multi-Layer Perceptron) com algoritmo de treinamento Levenberg-Marquardt backpropagation. A rede mostrou-se satisfatória, pois obteve um coeficiente de regressão próximo de um. Na etapa de classificação, a RNA, usando o algoritmo Levenberg-Marquardt backpropagation, através de uma classe binária, obteve um percentual de acertos acima de 93%, o que o classifica como bastante eficiente. Na análise da RNA, na etapa de agrupamento de dados utilizada para possíveis detecções de falhas, a rede utilizada foi a Kohonen onde foi avaliada a sensibilidade da rede em agrupar os dados com similaridade. Os parâmetros utilizados foram as vazões de diesel e contaminantes, pressão e temperatura. Numa segunda etapa foram inseridos erros na rede. A temperatura foi o parâmetro escolhido por ter maior susceptibilidade a erros de medição na indústria. O resultado obtido é representado por um mapa auto-organizável (SOM Self-Organizing Map) que identificou de forma satisfatória, através de cores, a falta de similaridade entre os dados inseridos na rede. As simulações desenvolvidas neste trabalho, bem como o treinamento da rede conseguiram representar adequadamente os processos estudados.

Submitted by isabela.moljf@hotmail.com (isabela.moljf@hotmail.com) on 2017-05-03T11:03:05Z No. of bitstreams: 1 lucianohonoratochagas.pdf: 8622580 bytes, checksum: 20a6210f264ae2b6015f16d383e48fb8 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-13T13:13:34Z (GMT) No. of bitstreams: 1 lucianohonoratochagas.pdf: 8622580 bytes, checksum: 20a6210f264ae2b6015f16d383e48fb8 (MD5) / Made available in DSpace on 2017-05-13T13:13:35Z (GMT). No. of bitstreams: 1 lucianohonoratochagas.pdf: 8622580 bytes, checksum: 20a6210f264ae2b6015f16d383e48fb8 (MD5) Previous issue date: 2013-11-22 / O grande interesse na hidrodessulfurização (HDS) de gasolina é realizar remoção profunda de enxofre e, ao mesmo tempo, reduzir a perda do numero de octanos que ocorre no processo de HDS minimizando a hidrogenação (HID) de olefinas, as quais são benéficas para a octanagem. Além do componente ativo e do promotor, o suporte deve ser considerado uma parte integral do catalisador. Nesse sentido, diversos suportes (incluindo aluminas e óxidos mistos) foram preparados a partir da calcinação de diferentes precursores. Uma amostra de Boehmita comercial foi usada como precursora de polimorfos de alumina. Para comparação, três outros precursores foram sintetizados a partir de diferentes métodos. Particularmente, o uso de excesso de ureia promoveu uma forma muito cristalina de carbonato básico de alumínio. Cada precursor foi calcinado em várias temperaturas gerando polimorfos de alumina, os quais foram analisados estruturalmente por DRX e RMN de 27Al. Devido ao interesse em suportes para catalisador, atenção especial foi dada à fase γ-Al2O3, a qual em adição a investigação estrutural foi submetida à análise textural. Essas quatro amostras de γ-Al2O3 foram utilizadas como suportes para catalisadores do tipo CoMo, que foram testados em reações de HDS de tiofeno e HID de cicloexeno. Os testes catalíticos mostraram que as atividades catalíticas crescem com o aumento do diâmetro médio de poros das fases CoMo/γ-Al2O3, e estão diretamente relacionados à dispersão do molibdênio sobre o suporte. Os resultados mostraram que a partir de diferentes rotas de síntese, e usando uma rota comum de calcinação, podem-se obter materiais com a mesma composição, mas com diferentes propriedades estruturais e texturais. Além disso, catalisadores do tipo CoMo suportados, contendo 20 % de MoO3 e 3 % de CoO, foram preparados por impregnação ao ponto úmido com soluções aquosas de molibdênio e cobalto sobre óxidos mistos obtidos a partir de hidrotalcitas. Os precursores contendo variadas quantidades de Mg, Co e Al ou Ni, Co e Al foram sintetizados pelo método de hidrólise de ureia. A calcinação leva a óxidos mistos cujas características estruturais dependem da composição. A caracterização dos suportes foi feita pelas técnicas de BET, DRX, RMN, IV, UV-vis/DRS e TPR. As amostras sulfetadas foram usadas como catalisadores em reações simultâneas de HDS de tiofeno e HID de cicloexeno. Os resultados foram comparados com catalisadores convencionais CoMo/γ-Al2O3, indicando que as atividades catalíticas dependem dos métodos de preparação dos precursores e suportes. Na série Mg-Co-Al o catalisador com maior quantidade de magnésio mostrou as maiores atividades de HDS e HID, sugerindo que a basicidade está associada com a performance catalítica. Adicionalmente, a amostra sem magnésio e contendo alta quantidade de cobalto exibiu as menores atividades e a maior seletividade (HDS/HID = 3,86). Os resultados indicam que o excesso de cobalto diminui a atividade enquanto a presença de magnésio contribui para aumentá-la. Por outro lado, a série Ni-Co-Al exibiu as menores razões HDS/HID. Nesse caso, as altas atividades para hidrogenação são atribuídas às altas quantidades de níquel. Adicionalmente, uma comparação entre catalisadores contendo 10 % de MoO3 e 3 % de CoO, suportados em óxidos mistos derivados de HDL e um catalisador suportado em alumina, revela que o suporte mais ácido tem maior influência sobre a capacidade de hidrogenação do catalisador. Entretanto, apesar da composição e das características estruturais dos suportes, o método de preparação pode influenciar significativamente no desempenho de um catalisador suportado. / The great interest in hydrodesulfurization (HDS) of gasoline is to perform a deep sulfur removal and, at the same time, to reduce the loss of the octane number occurring in the HDS process, by minimizing the hydrogenation of olefins which are beneficial to this property. Besides the active component and the promoter, the support has to be considered an integral part of the catalyst. In this sense, several supports (enclosing aluminas and mixed oxides) were prepared from calcination of different precursors. A commercial sample of Boehmite was used as precursor of alumina polymorphs. For comparison, three other precursors were synthesized from different methods. Particularly, the use of excess of urea promoted a very crystalline form of basic aluminum carbonate. Each precursor of alumina was calcined at various temperatures generating alumina polymorphs, which were structurally analyzed by XRD and 27Al MAS NMR. Due to interest in catalysis supports, special attention was given to the γ-Al2O3 phase, which in addition to structural investigation was subjected to textural analysis. These four γ-Al2O3 samples were used as catalyst supports like CoMo, which were tested in reactions of HDS of thiophene and HID of cyclohexene. The catalytic tests show that catalytic activities increase with pore diameters of CoMo/γ-Al2O3 phases and are directly related to dispersion of molybdenum on the support. The results showed that, from different synthesis procedures and common route of calcination, one can obtain materials with the same composition but with different structural and textural properties. Furthermore, supported CoMo catalysts containing 20 % of MoO3 and 3 % of CoO were prepared by incipient wetness impregnation of molybdenum and cobalt aqueous solutions over mixed oxides obtained from hydrotalcite precursors. The precursors, containing varying amounts of Mg, Co and Al or Ni, Co and Al cátions, were synthesized by urea hydrolysis method. The calcination led to mixed oxides whose structural characteristics depend on the composition. Characterization of the supports by BET, XRD, NMR, FTIR, UV-vis/DRS and TPR techniques was carried out. The sulfided samples were used as catalysts in simultaneous hydrodesulfurization of thiophene and hydrogenation of cyclohexene. The results were compared with conventional CoMo/γ-Al2O3 catalysts, which indicate that the catalytic activities depend on the preparation method of the precursors and supports. In the Mg-Co-Al series, the high magnesium content catalyst show higher HDS and HYD activities, suggesting that the support basicity is associated with catalytic performance. Furthermore, the free magnesium and high cobalt content catalyst show lower activities and higher selectivity (HDS/HYD = 3.86). The results indicate that the excess of cobalt decreases the activities while the presence of magnesium contributes to improve them. Otherwise, the Ni-Co-Al series show the smaller HDS/HYD ratios. In this case, the higher hydrogenation activities are assigned to high nickel content. Additionally, a comparison between catalysts containing 10 % of MoO3 and 3 % of CoO, supported on mixed oxides derived of LDH and a catalyst supported on alumina reveals that the most acidic support (alumina) has great influence over hydrogenation capacity of the catalyst. However, besides the composition and structural characteristics of the supports, the preparation method can to influence significantly the performance of a supported catalyst.

La diminution en pétrole brut léger nécessite de convertir les fractions lourdes en produits valorisables (essences, gazoles, huiles, etc.). Dans ce contexte, l'hydrocraquage (HCK) fournit des produits de très haute qualité à partir de distillats sous vide (DSV) du pétrole brut. La qualité des coupes obtenues est caractérisée par des propriétés physico-chimiques qui sont soumises à des spécifications. L'optimisation du procédé nécessite des expérimentations longues et coûteuses. IFPEN a donc de plus en plus recours à des tests sur unité d'expérimentation haut débit (EHD). Ces derniers posent cependant un problème d'accessibilité aux coupes d'intérêt. Par ailleurs, pour comprendre et prédire l'impact des conditions opératoires sur la qualité des produits, des simulateurs sont développés. Certaines propriétés de produits sont cependant complexes et difficiles à modéliser voire mal comprises. Ce travail de thèse a porté sur l'amélioration de la compréhension moléculaire des propriétés produits pour une meilleure prédiction. Dans cette étude, nous nous sommes focalisés sur le point de trouble (PT) de la coupe gazole et l'indice de viscosité (VI) de l'huile obtenue lors de l'hydrocraquage de DSV. Deux techniques d'analyse moléculaire ont été utilisées : la chromatographie en phase gazeuse bidimensionnelle (GC×GC) qui permet de déterminer la composition par famille chimique des différentes coupes et la résonance magnétique nucléaire (RMN) du 13C qui fournit des informations sur la structure chimique des hydrocarbures présents dans ces mélanges. Nous présentons les résultats obtenus par une régression multivariée parcimonieuse (sparse Partial Least Squares) appliquée aux données GC×GC et 13C RMN. Il s'agit d'une variante de la PLS classique qui permet de réduire le nombre de facteurs tout en privilégiant ceux qui sont les plus corrélés à une propriété d'intérêt donnée. Globalement, cette étude a notamment permis de mieux comprendre l'impact des différents hydrocarbures (n-paraffines, isoparaffines, aromatiques,…) et de leur structure moléculaire (longueur de chaînes, degrés de branchements,…) sur le PT des gazoles et le VI des huiles. La bonne qualité des modèles obtenus par sparse PLS montre par ailleurs la possibilité d'accéder à la qualité des produits lors de l'utilisation d'EHD. Des modèles de prédiction par krigeage ont également été développés. Cette méthode d'interpolation permet de prédire une propriété en un point donné en effectuant une moyenne pondérée des observations au voisinage de ce point. Les modèles de krigeage sont des modèles locaux adaptés aux structures de données complexes. Ce sont des approches probabilistes qui permettent d'estimer les incertitudes de prédiction. Aussi bien dans le cas du PT de la coupe gazole que dans celui du VI de la coupe huile, les résultats montrent une amélioration des performances. Cette approche est tout à fait novatrice dans le domaine des produits pétroliers. Lors de l'utilisation d'unités EHD, elle permet d'accéder au VI des huiles de base plus aisément que via des données chromatographiques ou spectroscopiques, qui sont de plus non accessibles en raffinerie / The rapid decline in light crude oils requires to convert heavy petroleum fractions into more valuable products (naphtha, diesel, lubricants, etc.). In this context, hydrocracking process (HCK) consists on upgrading vaccum gas oil (VGO) into high quality products. The quality of petroleum products is based on some chemical and physical properties that should fulfill prerequisite specifications. The hydrocracking process optimization requires to set up time consuming and costly experiments for developing catalysts and setting operating conditions. High throughput experimentation (HTE) units are then increasingly used at IFPEN. However, these units do not enable to obtain end products. Otherwise, predictive models were developed in order to understand and predict the impact of operating conditions about products quality. However, some complex properties are very difficult to model and require a better understanding. This work is mainly concerned with the understanding of diesel cloud point (CP) and viscosity index (VI) of base oils. Two analytical techniques were used: the two-dimensional gas chromatography (GC×GC) that enables to identify hydrocarbons compounds in petroleum products and the 13C nuclear magnetic resonance (NMR) spectroscopy which provides structural characteristics of these compounds. A sparse multivariate regression (sparse Partial Least Squares) was performed using chromatographic and spectroscopic data. The sparse PLS is derived from classical PLS. It allows to reduce the number of factors by performing a variable selection. The selected factors are the most correlated to the property to model. Globally, this approach enabled to better understand how hydrocarbon compounds (nparaffins, isoparaffins, aromatics,…) and their molecular characteristics (carbon number, degree of branching,…) affect the diesel CP and the VI of base oil. Furthermore, the good performances of developed sparse PLS models show that it is possible to access to the products quality when using HTE units. Kriging models were also developed. Kriging is an interpolation method that predicts the value of a function at a given point by computing a weighted average of the known values of the function in the neighborhood of the point. Kriging models have local aspect which is well adapted to complex data. Its probabilistic approach enables to provide an estimate of predicted value uncertainty. Results show that kriging improves predictive performances for both diesel CP and VI of base oil. This approach is quite innovative in modelling of petroleum products properties. When using HTE units, it allows to estimate the VI of base oil more easily than from chromatographic or spectroscopic data which are not available for the refiners

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, Iraq