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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.

This study aimed to investigate the feasibility of using several genetic techniques for identification of sulphate-reducing bacteria. A group of eight type strains (seven of which were <I>Desolfovibrio</I>) were used as test group for every method except RSGP, for which an established set of oil field isolates was used. Ribotyping involves restriction fragment length polymorphism (RFLP) analysis of ribosomal RNA (rRNA) operons. Hybridisation of <I>Eco </I>RI-digested genomic DNA to a PCR-amplified (500 bp) rRNA gene product resulted in generation of discriminatory RFLP patterns for all but two of the eight test strains. Restriction digestion of PCR-amplified (1400 bp) rRNA gene products (PCR-robotyping) allowed differentiation between all eight strains for two of the seven enzymes tested. Random amplified polymorphic DNA (RAPD) analysis allows PCR-generation of distinct sets ("fingerprints") of amplification products from genomic DNA templates. Nine oligonucleotide decamers were tested as primers, two of which were found to generate discriminatory profiles for each of the eight type strains. Hybridisation of 32P-labelled RAPD products against genomic DNA from eleven sulphate-reducing strains was found to result in specific hybridisation of probes to their complementary genomic DNA. Reversal of the hybridisation procedure, using 32P-labelled genomic DNA against immobilised RAPD probes, was found to allow analysis of mixed genomic DNA samples in a single step. This reverse method is very similar in principle to RSGP, which allows analysis of mixed genomic DNA preparations by hybridisation against a master filter of genomic DNAs from a series of environmental bacterial standards. This study developed a method to allow quantitation of RSGP hybridisation signals, and went on to analyse biofilm samples from various locations in Western Canadian oil fields, resulting in identification of 21% (average) of each mixed DNA sample.

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