Navegando por Assunto "Filtro de Kalman-Bucy"

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Acesso aberto (Open Access)
Aplicação do método de Kalman a dados geofísicos
(Universidade Federal do Pará, 1998-03-03) ROCHA, Marcus Pinto da Costa da; LEITE, Lourenildo Williame Barbosa; http://lattes.cnpq.br/8588738536047617
The Kalman filter is applied to the inverse filtefing or deconvolution problem. In this dissertation we applied the Kalman method, it is considered like a processament vition on time domain, to separet signal-noise within sonic perfil which is admited like no stationary stochastic process. In next work will survey deconvolution problem. The derivation given of the Kalman filter emphasizes the relationship between the Kalman and Wiener filter. This derivation is based on the modeling of randon processes as the output of linear systems excited by white noise. Ilustrative results indicate the applicability of these tchniques to a variety of geophysical data processing problems, for example the ideal well log teated here. The Kalman filter offters exploration geophysicists addtition insight into processing problem modeling and solution.
Acesso aberto (Open Access)
Atenuação de múltiplas e compressão do pulso fonte em dados de sísmica de reflexão utilizando o filtro Kalman-Bucy
(Universidade Federal do Pará, 2003-01-24) ROCHA, Marcus Pinto da Costa da; LEITE, Lourenildo Williame Barbosa; http://lattes.cnpq.br/8588738536047617
The main objective of this work is the study and the application of the Kalman-Bucy method in the processo f deconvolution to the impulse and deconvolution with prediction, considering the observed data as no stationary. The data used in this work are synthetic and, with this, this Thesis has characteristics of a numerical and search. The operator of deconvolution to the impulse is obtained from the Crump theory (1974), doing use of the solution of equation of Wiener-Holp presented by Kalman-Bucy in the continuoun and discrete forms considering the stacionary process. The prediction operator (KBCP) is based the Crump (1974) and Mendel et al (1979) theorics. Its structure resembles the Wiener-Hopf filter, where the coefficients of the operator are obtained through the autocorrelation, in the case (KBCP) are obtained from the function bi(k). The problem is defined in two steps: the first consists of the generation of the signal, and second of its evaluation. The deconvolution performed is classified as statistics, and is a model based in the properties of the registered signal and its representation. The method were applied only in synthetic data with common-shot section obtained from models with continuous interfaces and homogeneous layers.
Acesso aberto (Open Access)
Deconvolução de processo sísmico não-estacionário
(2000-03) LEITE, Lourenildo Williame Barbosa; ROCHA, Marcus Pinto da Costa da
The present paper treats the application of the Kalman-Bucy filter (KBF), organized as a deconvolution (KBDF), for the extraction of the reflectivity function from seismic data. This means that the process is described as non-stationary, and corresponds to a generalization of the Wiener-Kolmogorov theory. The mathematical description of the KBF preserves its relationship to the Wiener-Hopf filter (WHF) that deals with the counterpart stationary stochastic process. The strategy to solve the problem is structured in parts: (a) The optimization criterion; (b) The a priori knowledge; (c) The algorithm; and (d) The quality. The a priori knowledge includes the convolutional model, and establishes statistics to its components (effective source wavelet, reflectivity function, and geological and local noises). To demonstrate the versatility, applicability and limitations of the method, we performed systematic deconvolution experiments under several situations of additive noise levels and effective source wavelet. First, we demonstrate the necessity of equalizer filters, and second that the spectral coherence factor is a good measure of the quality of the process. We also justify the present study for its application in real data, as exemplified.
Acesso aberto (Open Access)
Treatment of geophysical data as a non-stationary process
(2003) ROCHA, Marcus Pinto da Costa da; LEITE, Lourenildo Williame Barbosa
The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.