Made available in DSpace on 2018-08-01T21:36:53Z (GMT). No. of bitstreams: 1 tese_10765_Dissertação_final_Rayza.pdf: 2180620 bytes, checksum: 5e88e543a5adef7347618d2eef3cfb62 (MD5) Previous issue date: 2017-03-27 / A calibração multivariada associada à técnica de infravermelho é uma alternativa aos métodos tradicionais para determinação de parâmetros físico-químicos em petróleo. Entretanto, o modelo multivariado construído é aplicável somente para o instrumento no qual os espectros foram obtidos. A transferência de calibração de modelos multivariados é de fundamental importância para a indústria petrolífera, levando-se em conta que aumenta a aplicabilidade de modelos e permite estimar com rapidez e com poucos gastos diversas propriedades físico-químicas. Este trabalho foi dividido em duas seções: a primeira é dedicada à avaliação modelos de transferência entre dois instrumentos de infravermelho a região média (MIR) para modelos PLS (mínimos quadrados parciais) e OPLS (projeções ortogonais em estruturas latentes); e a segunda visa aplicar a transferência PDS (padronização direta por partes) a modelos PLS para predição de densidade API, TIAC (temperatura de início de aparecimento de cristais), NAT (número de acidez total) e NAN (número de acidez naftênica). Dentre os métodos quimiométricos SBC (correção de declive e viés), FR (recalibração total), DS (padronização direta) e PDS avaliados para previsão de densidade API, o modelo de transferência PDS aplicado ao modelo OPLS resultou na melhor capacidade preditiva (RMSEP de 1,48). A aplicação direta de PDS a um modelo PLS original conta com a vantagem de aproveitar modelos já consolidados, e os resultados da primeira seção indicam que isto é uma possibilidade. Na segunda seção, as propriedades API, TIAC, NAT e NAN foram modeladas e validadas por PLS para o instrumento primário. Espectros secundários, diferentes daqueles da primeira seção, passaram por uma interpolação polinomial a fim de igualar as variáveis às do instrumento primário, antes da aplicação da transferência PDS. Os espectros transferidos e processados por airPLS, técnica iterativa adaptativa, se tornaram indistiguíveis por PCA (análise por componentes principais) dos espectros primários. A técnica de PDS associada a modelos PLS mostrou-se promissora, especialmente sendo capaz de estimar com boa exatidão o valor da densidade API de amostras de petróleo classificadas como medianas.

Crude oil leakages often give rise to in situ contamination with both oil and salt. In this study, the biodegradation of model alkanes and of saturated hydrocarbons in whole crude oil by hydrocarbon-degrading bacteria was investigated at different salt (NaCl, KCl, Na2SO4) concentrations. Changes in cell surface hydrophobicity at different NaCl concentrations were also investigated. The results show that with increasing NaCl concentration, the lag phase for strain growth on hydrocarbons was prolonged; however, the total degradation efficiency was not influenced greatly. The formation of different sizes of cell aggregates at different salt concentrations indicated that salt could indirectly influence mass transfer of hydrocarbons from the medium to the interior of the cells. The results also showed that KCl had a less inhibitory effect on biodegradation than NaCl, and changes of Na2SO4 concentration did not greatly affect biodegradation. In addition, cell surface hydrophobicity increased with increasing NaCl concentration when the cultures were grown on hydrocarbons.

Crude oil is a complex mixture of aromatic and aliphatic hydrocarbons of diverse molecular weight. In spite of its high hydrophobicity and toxicity, crude oil is a rich source of carbon for microorganisms. It has been proposed that microbial metabolism contributes to petroleum physicochemical characteristics, as highly specialized microorganisms are adapted to its extreme conditions. Deciphering these unique microbiomes will allow more in-depth characterization of crude oil and better understand its chemistry. The general aim of this study is to characterize the unique microbial communities of crude oil through a comparative metagenomics approach. I performed a survey of worldwide crude oil metagenomes in literature and databases. I identified 48 metagenomics datasets from five countries. The Comparative analysis of these metagenomes allowed us to identify how Methanogens are predominant in the North-American crude oil, being Methanoculleus and Methanosaeta the dominant genera in Canada and Methanothermococcus the predominant genus in the United States oil fields. In the case of Nigeria crude oil, Marinobacterium and Parvivaculum were the two dominant genera. In the case of Thailand, the dominant genus Thermus reflected the high-temperature environment of that oil field. Finally, metagenomes from China were the most diverse, reflecting the heterogeneity of the oil fields from that country. I generated metagenomics data from 27 Saudi Arabian crude oil samples originated in 6 different oil fields. As no crude oil metagenome has been reported yet for the Arabian Peninsula, the information provided in this dissertation is contributing towards a complete worldwide characterization of crude oils. Two genera, Peanibacilus and Thermospira, are proposed as the taxonomic markers for the set of Saudi crude oil analyzed. In this thesis I elucidated the structure of microbial communities in crude oils globally, suggesting that it may reflect the geological history of crude oils. This study sheds light on the importance of microorganisms for understanding petroleum geobiology. These findings suggest that it is possible to identify the distinctive microbiota associated with specific types of crude oil according to its location. The results presented here set the basis for developing novel methodologies for crude oil identification based on a microbial fingerprinting approach.

This study compares different methods of forecasting price volatility in the crude oil futures market using daily data for the period November 1986 through March 1997. It compares the forward-looking implied volatility measure with two backward-looking time-series measures based on past returns - a simple historical volatility estimator and a set of estimators based on the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) class of models. Tests for the relative information content of implied volatilities vis-à-vis GARCH time series models are conducted within-sample by estimating nested conditional variance equations with returns information and implied volatilities as explanatory variables. Likelihood ratio tests indicate that both implied volatilities and past returns contribute volatility information. The study also checks for and confirms that the conditional Generalized Error Distribution (GED) better describes fat-tailed returns in the crude oil market as compared to the conditional normal distribution. Out-of-sample forecasts of volatility using the GARCH GED model, implied volatility, and historical volatility are compared with realized volatility over two-week and four-week horizons to determine forecast accuracy. Forecasts are also evaluated for predictive power by regressing realized volatility on the forecasts. GARCH forecasts, though superior to historical volatility, do not perform as well as implied volatility over the two-week horizon. In the four-week case, historical volatility outperforms both of the other measures. Tests of relative information content show that for both forecast horizons, a combination of implied volatility and historical volatility leaves little information to be added by the GARCH model. / Master of Arts

The history of crude oil desalting/dehydration plant (DDP) has been marked in progressive phases-the simple gravity settling phase, the chemical treatment phase, the electrical enhancement phase and the dilution water phase. In recent times, the proper cachet would be the control-optimisation phase marked by terms such as "DDP process control", "desalter optimisation control" or "DDP automating technology". Another less perceptible aspect, but nonetheless important, has been both a punch listing of traditional plant boundaries and a grouping of factors that play the essential roles in a desalting/dehydration plant (DDP). Nowadays, modelling and optimising of a DDP performance has become more apparent in petroleum and chemical engineering, which has been traditionally concerned with production and refinery processing industries. Today's desalting/dehydration technology finds itself as an important factor in such diverse areas as petroleum engineering, environmental concerns, and advanced technology materials. The movement into these areas has created a need not only for sources useful for professionals but also for gathering relevant information essential in improving product quality and its impact on health, safety and environmental (HSE) aspects. All of the foregoing, clearly establishes the need for a comprehensive knowledge of DDP and emulsion theories, process modelling and optimisation techniques. The main objective of this work is to model and qualitatively optimise a desalting/dehydration plant. In due course, the contents of this thesis will cover in depth both the basic areas of emulsion treatment fundamentals, modelling desalting/dehydration processes and optimising the performance of desalting plants. In addition, emphasis is also placed on more advanced topics such as optimisation technology and process modifications. At the results and recommendation stage, the theme of this work-optimising desalting/dehydration plant will practically be furnished in an applicable scheme. Finally, a significant compendium of figures and experimental data are presented. This thesis, therefore, essentially presents the research and important principles of desalting/dehydration systems. It also gives the oil industry a wide breadth of important information presented in a concise and focused manner. In search of data quality and product on-line-improvement, this combination will be a powerful tool for operators and professionals in a decision support environment.

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Heat-integrated crude oil distillation systems are energy and capital intensive, and have a very complex structure with strong interactions between the individual units. Retrofit of these systems is of major interest to petroleum refiners. Retrofit objectives are various and preferably achieved with minimum capital expenditure, while equipment constraints are met. Traditional approaches to retrofit design of crude oil distillation systems identify promising modifications based on experience or pinch analysis. Later, sequential approaches to retrofit design were developed, in which distillation and heat recovery units are modified individually. Recent approaches considered simultaneously the distillation column and heat integration targets, rather than the existing heat recovery system. That shortcut models for retrofit design of distillation columns are not available is an additional limitation of established methodologies. In this thesis, a new approach is presented for retrofit design of heat-integrated crude oil distillation systems. Shortcut models are developed for distillation retrofit, including reboiled and steam-stripped columns. These models are based on the Underwood equation and are appropriate for retrofit design of simple columns and various complex column arrangements. Models are also proposed for exchanger network retrofit, addition of new columns to the existing distillation unit, modifying column internals, enhancing heat transfer in exchanger tubes and for evaluating CO2 emissions in existing crude oil distillation units. The retrofit design methodology is optimisation-based, and considers the existing distillation process simultaneously with the details of the associated heat recovery system. Existing equipment limitations, such as the hydraulic capacity of the distillation column, exchanger network pressure drop and bottlenecked exchangers, are accounted for. The approach considers various structural modifications and design options resulting in significant benefits. Examples of these are the installation of preflash and prefractionator units to the existing column configuration, replacement of column internals with packing, enhancement of exchanger heat transfer and integration of a gas turbine with an existing furnace. The optimisation framework comprises column and exchanger network retrofit models, cost models and suitable objective functions. The approach optimises all operating conditions of the existing distillation process and any new columns to minimise or maximise a specified objective function, while satisfying existing constraints. The objective function is flexible and varies according to retrofit objectives. Several objectives are taken into account, such as reducing energy consumption and overall cost, increasing capacity, improving profit and reducing CO2 emissions. The approach allows these objectives to be met by considering several design alternatives. The new retrofit approach is applied to different industrial cases of crude oil distillation units, for energy and total cost savings, throughput enhancement, product yield changes, profit increase and emissions reduction. Typical results conclude that retrofit goals can be achieved with substantial savings in energy and total cost, and improved profit with minimal capital investment.

Arbuscular mycorrhizal fungi (AMF) can play an important role in the phytoremediation of petroleum hydrocarbon (PH)-contaminated soil. However, little is known about the effects of AMF in combination with biostimulation via fertilization or bioaugmentation with hydrocarbonoclastic microorganisms, during phytoremediation of PH in soils. This research evaluated the influence of the AMF Glomus intraradices and inorganic fertilization on growth and physiological responses of Lolium multiflorum Lam. cv. Passarel Plus during phytoremediation of soil contaminated with Arabian medium crude oil (ACO). Also determined was the interaction of AMF with the hydrocarbonoclastic bacterium, Sphingomonas paucimobilis EPA505 (Sp), and the filamentous fungus, Cunninghamella echinulata var. elegans ATCC-36112 (Ce), on growth and selected physiological responses of L. multiflorum during phytoremediation of soil contaminated with benzo[a]pyrene (BaP) or ACO. This research provides evidence that AMF enhance the phytoremediation of petroleum hydrocarbons in soils when inoculated with L. multiflorum. The concentration of petroleum hydrocarbons in soil was a determining factor of potential benefits of AMF on L. multiflorum. Low (3000 mg·kg-1) or high (15000 mg·kg-1) concentrations of ACO resulted in limited benefits of AMF on plant growth, physiology, and degradation of ACO in soil. However, when plants were exposed to an intermediate ACO concentration in soil (6000 mg·kg-1), AMF plants had enhanced growth, physiological responses, and greater ACO-degradation than non-AMF plants. The AMF symbiosis in roots of plants was observed at all concentrations of ACO-contaminated soil. This research is one of the first reports demonstrating the benefits of AMF on the degradation of benzo[a]pyrene or ACO, alone or in combination, with the hydrocarbonoclastic microorganisms. Thus, AMF resulted in a beneficial synergism with the hydrocarbonoclastic microorganisms, particularly during ACO-degradation in the rhizosphere of L. multiflorum. Hydrocarbonoclastic microorganisms had no negative effects on AMF colonization.