2 resultados para Runs of homozygosity

em Memorial University Research Repository


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Water-alternating-gas (WAG) is an enhanced oil recovery method combining the improved macroscopic sweep of water flooding with the improved microscopic displacement of gas injection. The optimal design of the WAG parameters is usually based on numerical reservoir simulation via trial and error, limited by the reservoir engineer’s availability. Employing optimisation techniques can guide the simulation runs and reduce the number of function evaluations. In this study, robust evolutionary algorithms are utilized to optimise hydrocarbon WAG performance in the E-segment of the Norne field. The first objective function is selected to be the net present value (NPV) and two global semi-random search strategies, a genetic algorithm (GA) and particle swarm optimisation (PSO) are tested on different case studies with different numbers of controlling variables which are sampled from the set of water and gas injection rates, bottom-hole pressures of the oil production wells, cycle ratio, cycle time, the composition of the injected hydrocarbon gas (miscible/immiscible WAG) and the total WAG period. In progressive experiments, the number of decision-making variables is increased, increasing the problem complexity while potentially improving the efficacy of the WAG process. The second objective function is selected to be the incremental recovery factor (IRF) within a fixed total WAG simulation time and it is optimised using the same optimisation algorithms. The results from the two optimisation techniques are analyzed and their performance, convergence speed and the quality of the optimal solutions found by the algorithms in multiple trials are compared for each experiment. The distinctions between the optimal WAG parameters resulting from NPV and oil recovery optimisation are also examined. This is the first known work optimising over this complete set of WAG variables. The first use of PSO to optimise a WAG project at the field scale is also illustrated. Compared to the reference cases, the best overall values of the objective functions found by GA and PSO were 13.8% and 14.2% higher, respectively, if NPV is optimised over all the above variables, and 14.2% and 16.2% higher, respectively, if IRF is optimised.

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The problems faced by scientists in charge of managing Atlantic salmon (Salmo salar) stocks are : i) how to maintain spawning runs consisting of repeat spawners and large multi-sea-winter (MSW) adults in the face of selective homewater and distant commercial fisheries and , ii) how to more accurately predict returns of adults. Using data from scales collected from maiden Atlantic salmon grilse from two locations on the Northern Peninsula of Newfoundland, St. Barbe Bay and Western Arm Brook, their length at smolting was back calculated. These data were then used to examine whether the St. Barbe commercial fishery is selective for salmon of particular smolt age and/or size. Analysis indicated that come commercial fishery selected larger, but not necessarily older adults that those escaping to Western Arm Brook over the period of this study, 1978-1987. It was determined that less than average size smolts survived better than above average size smolts. Slection for repeat spawners, large MSW salmon, and larger grilse has meant reductions in the proportions of these adults in the spawning runs on Western Arm Brook. This may impact the Western Arm Brook salmon stock by increasing the population instability. Sea survival was significantly correlated with selection by the commercial fishery. Characteristics of adults in Western Arm Brook during the period of study (1978-1987) did not help in explaining yearly variation in sea survival. The characteristics of smolts, however, when subjected to multiple regression analysis explained 57.2 percent of the yearly variation in sea survival.