Crude oil prices impact the world economy and are thus of interest to economic experts and politicians. Oil price’s volatile behaviour, which has moulded today’s world economy, society and politics, has motivated and continues to excite researchers for further study. This volatile behaviour is predicted to prompt more new and interesting research challenges. In the present research, machine learning and computational intelligence utilising historical quantitative data, with the linguistic element of online news services, are used to predict crude oil prices via five different models: (1) the Hierarchical Conceptual (HC) model; (2) the Artificial Neural Network-Quantitative (ANN-Q) model; (3) the Linguistic model; (4) the Rule-based Expert model; and, finally, (5) the Hybridisation of Linguistic and Quantitative (LQ) model. First, to understand the behaviour of the crude oil price market, the HC model functions as a platform to retrieve information that explains the behaviour of the market. This is retrieved from Google News articles using the keyword “Crude oil price”. Through a systematic approach, price data are classified into categories that explain the crude oil price’s level of impact on the market. The price data classification distinguishes crucial behaviour information contained in the articles. These distinguished data features ranked hierarchically according to the level of impact and used as reference to discover the numeric data implemented in model (2). Model (2) is developed to validate the features retrieved in model (1). It introduces the Back Propagation Neural Network (BPNN) technique as an alternative to conventional techniques used for forecasting the crude oil market. The BPNN technique is proven in model (2) to have produced more accurate and competitive results. Likewise, the features retrieved from model (1) are also validated and proven to cause market volatility. In model (3), a more systematic approach is introduced to extract the features from the news corpus. This approach applies a content utilisation technique to news articles and mines news sentiments by applying a fuzzy grammar fragment extraction. To extract the features from the news articles systematically, a domain-customised ‘dictionary’ containing grammar definitions is built beforehand. These retrieved features are used as the linguistic data to predict the market’s behaviour with crude oil price. A decision tree is also produced from this model which hierarchically delineates the events (i.e., the market’s rules) that made the market volatile, and later resulted in the production of model (4). Then, model (5) is built to complement the linguistic character performed in model (3) from the numeric prediction model made in model (2). To conclude, the hybridisation of these two models and the integration of models (1) to (5) in this research imitates the execution of crude oil market’s regulators in calculating their risk of actions before executing a price hedge in the market, wherein risk calculation is based on the ‘facts’ (quantitative data) and ‘rumours’ (linguistic data) collected. The hybridisation of quantitative and linguistic data in this study has shown promising accuracy outcomes, evidenced by the optimum value of directional accuracy and the minimum value of errors obtained.

The crude oil phenomenon has always been a big issue and the current situation does not prove different. Crude oil as a commodity is indisputably considered as one of the most utilized energy source as well as production input which enters into economic processes in the vast majority of countries over the world. The aim of this masters thesis is to provide a detailed description and analysis of the crude oil world market. Furthermore it not only gives a characteristics of the commodity and its energy use it also defines the market and its participants crude oil pricing crude oil trading and it also provides an analysis of the world oil demand as well as supply.The purpose of this masters thesis is among other to thoroughly analyze the crude oil prices development and introduce the contemporary trends present on the market. In the latter part of this thesis there will be a crude oil prices time series modelled and probable future price direction outlined. Moreover the thesis will reflect on the current oil prices drop with its possible effect on world economy.

Aim of this thesis was finding out whether there is asymmetry on gasoline market in Czech republic, which is common knowledge or if asymmetry is only illusion. With daily data about gasoline and diesel prices from CZ market and also daily Brent Crude Oil price, thesis tires to prove that there is no asymmetry on the market. Analysis was done with asymmetric error correction model and further testing of asymmetry with koeficients from ECM. Results yield that both gasoline and diesel markets show rather symmetrical reaction on entry price change. Asymmetry was proven only in few lags and final statement is that asymmetry on market in Czech republic is rather illusion then reality.

The current shortage of crude oil from conventional sources has increased interest in developing unconventional resources such as oil sands. Heavy crudes and bitumen are found in Northern Alberta and their exploration, processing, and transport to market pose challenges in the use of these resources. Part of the solution to these challenges involves the reactive thermal processing of heavy crudes and bitumen. This thesis focused on mild thermal cracking reactions, and two studies regarding these reactions were presented. The first was an experimental study performed in a pilot-scale semi-batch reactor. The three crude oils were heated to 350, 400, 425, and 450°C at 1240 kPa. A five-lump reaction model combined with a process simulator with VLE calculations was fitted with the experimental data obtained. The goodness of fit between the model predicted values and experimental values for the Hardisty (MBL), Albian Heavy Synthetic (AHS), and Christina Lake Dilute Bitumen (CDB) were determined to be 0.99, 0.99, and 0.98, respectively. Moreover, 80, 85, and 89% of the optimized model’s predicted values had less than 10% error for MBL, AHS, and CDB, respectively. The second study described the implementation of a mild thermal cracking reaction model to the development of a train car fire-model for the assessment of safety aspects in the design of train cars used to transport crude oil. Case studies were conducted using the UniSim® depressuring utility and a previously developed mild thermal cracking reaction model to demonstrate the effect of compositional change. Three crude oils with varying properties and representative of the types of crudes transported by rail in Canada were used here: MBL, AHS, and CDB. The case studies conducted showed the performance of a train car fire-model to be dependent on the crude oil characteristics: up to -57% and -99% difference in model predicted variables for AHS and CDB, respectively, when compared to MBL. Furthermore, the model’s performance was also shown to be affected by the compositional change of a given crude oil due to mild thermal cracking reactions: up to 42% difference in model predicted variables when compared to the base case.

Aus der Einleitung: "Ein wachsender Bedarf an nachhaltig verfügbaren Rohstoffen und knapper werdende Rohölressourcen steigern die wirtschaftliche Bedeutung natürlicher Faserstoffe. Das eröffnet neue, über den traditionellen Einsatz von Papier hinausgehende Anwendungen für cellulosische Fasern, beispielsweise in maßgeschneiderten 3D-Verpackungslösungen, im Leichtbau oder in Konstruktionswerkstoffen. Bei der Erschließung neuer Anwendungsbereiche steht neben der zentralen Kostenfrage das Ziel im Vordergrund, die Bauteile technologisch effizient herzustellen. Dafür sollen weitestgehend etablierte Technologien für die Verarbeitung der eingesetzten Halbzeuge einsetzbar sein, z.T. sind aber auch neue Technologien erforderlich, wie z.B. integriertes Fügen und Umformen. Diese Entwicklungen sind nicht auf die oft als Vorreiter angesehene Automobilbranche beschränkt, sondern betreffen z.B. auch die Möbelbranche, die Baustoffindustrie und zunehmend auch die Papierwirtschaft. ..."

Die Forschungsarbeit beschäftigte sich mit der Frage, ob es zielführend ist, die Mongolei durch Veredelung eigener Ölressourcen mit Mineralölprodukten zu versorgen. Die Mongolei ist ein Land mit großem mineralischen Rohstoffpotential, darunter auch Erdöl. Zurzeit wird der Bedarf an Mineralölprodukten ausschließlich durch Import gedeckt. Zur Untersuchung der technischen Machbarkeit einer Ölverarbeitungsindustrie wurden verschiedene Raffinieriekonzepte auf Basis des mongolischen Rohöls Tamsag erarbeitet. Anschließend wurde anhand einer Bewertungsmethode die gesamtwirtschaftliche Relevanz der Downstream-Industrie in der Mongolei geprüft. Im Ergebnis der Untersuchungen zeigte sich, dass eine Erdölindustrie für die Mongolei sinnvoll ist. Die Erdölveredelung, als neuer Wirtschaftszweig, würde Möglichkeiten wirtschaftlicher Entwicklung eröffnen und die Importabhängigkeit der strategisch wichtigen Mineralölprodukte vermeiden.

Some of anaerobic, mesophilic sulfate-reducing bacteria that produce H₂S and cause microbial metal corrosion can degrade crude oil in anaerobic conditions. In this study, a mesophilic sulfate-reducing bacterial strain D107G3 isolated from Bach Ho gas-oil field in Vung Tau, Vietnam that is able to utilize crude oil in the anaerobic condition is reported. The strain D107G3 was classified as a Gram-negative bacterium by using Gram staining method. Basing on scanning microscopy observation, the cell of a strain D107G3 had a curved rod shape. The 16S rRNA gene sequence analysis showed that the strain D107G3 was identified as Desulfovibrio vulgaris with 99.7% identity. The suitable conditions for its growth that was determined via estimating its H₂S production was the modified Postgate B medium containing 1% (v/v) crude oil, 1% NaCl (w/v), pH 7 and 300C incubation. In these conditions, the strain D107G3 can consume 11.4 % of crude oil total and oxidize heavy crude oil (≥ C45) for one month at anoxic condition. These obtained results not only contribute to the science but also continue to warn about the dangers of mesophilic sulfate reducing bacteria to the process of crude oil exploitation, use, and storage in Vung Tau, Vietnam. / Trong bài báo này, chủng vi khuẩn khử sunphat (KSF) ưa ấm D107G3 phân lập từ giếng khoan dầu khí mỏ Bạch Hổ, Vũng Tàu, Việt Nam có khả năng sử dụng dầu thô trong điều kiện kị khí được công bố. Chủng D107G3 được xác định là vi khuẩn Gram âm nhờ phương pháp nhuộm Gram. Quan sát trên kính hiển vi điện tử quét cho thấy tế bào chủng D107G3 có hình que cong. Kết quả phân tích trình tự gen 16S rRNA đã xác định được chủng D107G3 thuộc loài Desulfovibrio vulgaris với độ tương đồng 99.7%. Thông qua đánh giá lượng H₂S tạo thành đã khám phá được điều kiện thích hợp cho sinh trưởng của chủng D107G3: môi trường Postgate B cải tiến chứa 1% (v/v) dầu thô, 1 % NaCl (gL⁻¹), pH 7 và nuôi cấy ở 30°C. Trong điều kiện đó, chủng D107G3 đã sử dụng được 11.4 % hàm lượng dầu tổng số, thành phần dầu bị phân huỷ là các n-parafin có mạch C≥45 sau 1 tháng nuôi cấy kỵ khí. Các kết quả này đóng góp về mặt khoa học và tiếp tục cảnh báo mối nguy hại của KSF ưa ấm đến việc khai thác, sử dụng và bảo quản dầu mỏ ở Vũng Tàu, Việt Nam.

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Recently, based on the physics of viscosity, we developed a new technology, which utilizes electric or magnetic fields to change the rheology of complex fluids to reduce the viscosity, while keeping the temperature unchanged. The method is universal and applicable to all complex fluids with suspended particles of nano-meter, sub-micrometer, or micrometer size. Completely different from the traditional viscosity reduction method, raising the temperature, this technology is energy-efficient, as it only requires small amount of energy to aggregate the suspended particles. In this thesis, we will first discuss this new technology in detail, both in theory and practice. Then, we will report applications of our technology to energy science research. Presently, 80% of all energy sources are liquid fuels. The viscosity of liquid fuels plays an important role in energy production and energy conservation. With an electric field, we can reduce the viscosity of asphalt-based crude oil. This is important and useful for heavy crude oil and off-shore crude oil production and transportation. Especially, since there is no practical way to raise the temperature of crude oil inside the deepwater pipelines, our technology may play a key role in future off-shore crude oil production. Electrorehology can also be used to reduce the viscosity of refinery fuels, such as diesel fuel and gasoline. When we apply this technology to fuel injection, the fuel droplets in the fuel atomization become smaller, leading to faster combustion in the engine chambers. As the fuel efficiency of internal combustion engines depends on the combustion speed and timing, the fast combustion produces much higher fuel efficiency. Therefore, adding our technology on existing engines improves the engine efficiency significantly. A theoretical model for the engine combustion, which explains how fast combustion improves the engine efficiency, is also presented in the thesis. / Physics

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