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.

Modeling the transport and fate of spilled crude oil is important for estimating short and long-term toxicity effects in coastal ecosystems. This research project investigates the partitioning of hydrocarbons from a surface crude oil slick, the resurfacing of chemically dispersed crude oil droplets, the suitability of in-situ field instruments for oil and sediment characterization, and the aggregation and settling of dispersed oil and suspended sediments. An initial laboratory study was conducted to investigate apparent hydrocarbon solubility in petroleum/water systems. Mixing shear and initial crude oil layer thickness were related empirically to oil entrainment rate. A model describing hydrocarbons partitioned in colloidal and soluble phases was consistent with experimental data. A second laboratory study was conducted to investigate the influence of coalescence kinetics on mean droplet size and resurfacing rate of chemically dispersed crude oil droplets. Increased mean shear rates resulted in mean droplet diameters and oil resurfacing rates. A third laboratory study was conducted to compare particle size and fractal dimension measurements obtained using a submersible flow cytometer, an electrozone particle counter, and a light scattering particle sizer. Measured particles included latex beads, crude oil, clay, crude oil-clay aggregates, and crude oil-silica aggregates. Tested instruments gave consistent size measurements for all particle systems, suggesting their suitability for sizing marine particles. To describe the aggregation kinetics of oil-sediment systems, a modified Smoluchowski model based on coalesced sphere (CS) assumptions was developed. Observed collision efficiency values (αOBS) were related to collision efficiency values for single particle type systems (αHOMO) and those for two particle type systems (αHET) using a probabilistic approach. For clay and crude oil, αHOMO values were higher than the αHOMO value for silica. Clay-oil and silica-oil have similar αHET values. Thus, crude oil can significantly increase the aggregation rates of noncohesive sediments such as silica. The CS model above was modified to incorporate sediment fractal geometry. The ability of this modified coalesced fractal sphere (mCFS) model to fit experimental data sets was better than that of a coalesced sphere (CS) model. Because of their reduced settling rates, sediments with lower fractal dimension form more aggregate with dispersed oil.

The purpose of this study is to isolate and identify the crude oil-degrading bacteria from oil polluted soil. Their physiological characteristics and oil-degrading capability were also studied. Eight polluted soil samples were taken from the Kaohsiung Refingery Factory of the Chinese Petroleum Corporation (CPC). The microbiota of the Kaohsiung refinery soil sample P37-2 (#6) could degrade crude oil from 2000 ppm to 572 ppm in 10 days. Bacteria in polluted soil samples were selected and isolated by minimal medium with 2000 ppm crude oil as the sole carbon source. Biochemical test, PCR-DGGE, and 16S DNA sequencing were used to identify and characterize the bacteria isolates. Three strains were identified as Pseudomonas aeruginosa (NSYSU-1-1), Acinetobacter sp. (NSYSU-4-1), and Pseudomonas sp. (NSYSU-7-1). These three strains and microbiota #6 were tested for their capability of degrading the total petroleum hydrocarbons (TPH). We found that microbiota #6 performed better than the other three bacterial strains in degrading the crude oil. In this study, we also found temperature was not the major factor of influcing the biodegradation; however, high oxygen concentration and providing nitrogen soure couled improve the biodegradation rate. Although both NSYSU-1-1 and NSYSU-7-1 are Pseudomonas strains, they performed different on degrading the oil. All strains tested could degrade the crude oil to a concentration below 1000 ppm to meet the government emission standard. The bacterial strains and techniques developed in this study provide a choice for future bioremediation of crude oil pollution.

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