Identificação e comparação entre controle preditivo com modelo não linear e PI sintonizados com PSO em sistema de separação gravitacional de águia-óleo

The separation methods are reduced applications as a result of the operational costs, the low output and the long time to separate the uids. But, these treatment methods are important because of the need for extraction of unwanted contaminants in the oil production. The water and the concentration of oil in water should be minimal (around 40 to 20 ppm) in order to take it to the sea. Because of the need of primary treatment, the objective of this project is to study and implement algorithms for identification of polynomial NARX (Nonlinear Auto-Regressive with Exogenous Input) models in closed loop, implement a structural identification, and compare strategies using PI control and updated on-line NARX predictive models on a combination of three-phase separator in series with three hydro cyclones batteries. The main goal of this project is to: obtain an optimized process of phase separation that will regulate the system, even in the presence of oil gushes; Show that it is possible to get optimized tunings for controllers analyzing the mesh as a whole, and evaluate and compare the strategies of PI and predictive control applied to the process. To accomplish these goals a simulator was used to represent the three phase separator and hydro cyclones. Algorithms were developed for system identification (NARX) using RLS(Recursive Least Square), along with methods for structure models detection. Predictive Control Algorithms were also implemented with NARX model updated on-line, and optimization algorithms using PSO (Particle Swarm Optimization). This project ends with a comparison of results obtained from the use of PI and predictive controllers (both with optimal state through the algorithm of cloud particles) in the simulated system. Thus, concluding that the performed optimizations make the system less sensitive to external perturbations and when optimized, the two controllers show similar results with the assessment of predictive control somewhat less sensitive to disturbances

Comparação de desempenho da deconvolução preditiva multicanal e da filtragem f-k na atenuação de múltiplas do fundo do mar

The seismic reflection is used on a large scale in oil exploration. In case of marine acquisition the presence of high impedance contrast at the interfaces water/air generates multiple reflections events. Such multiple events can mask primary events; thus from the interpretational viewpoint it is necessary to mitigate the multiples. In this manuscript we compare two methods of multiple attenuation: the predictive multichannel deconvolution (DPM) and the F-K filtering (FKF). DPM is based in the periodicity of the multiples while FKF is based in multiples and primaries splitting in F-K domain. DPM and FKF were applied in common-offset and CDP gathers, respectively. DPM is quite sensible to the correct identification of the period and size of the filter while FKF is quite sensible to an adequate choice of the velocity in order to split multiples and primaries events in the F-K domain. DPM is a method that is designed to act over a specific event. So, when the parameters are well selected, DPM is very efficient in removing the specified multiple. Then DPM can be optimized by applying it several times, each time with a different parameterization. A deficiency of DPM occurs when a multiple is superposed to a primary event: in this situation, DPM can attenuate also the primary event. On the other hand, FKF presents almost the same performance to all multiples that are localized in the same sector of the F-K domain. The two methods can be combined in order to take advantage of their associated potentials. In this situation, DPM is firstly applied, with a focus in the sea bed multiples. Then FKF is applied in order to attenuate the remaining multiples