Título: | EVALUATING THE IMPACT OF THE INFLATION FACTORS GENERATION FOR THE ENSEMBLE SMOOTHER WITH MULTIPLE DATA ASSIMILATION | ||||||||||||
Autor: |
THIAGO DE MENEZES DUARTE E SILVA |
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Colaborador(es): |
SINESIO PESCO - Orientador ABELARDO BORGES BARRETO JR - Coorientador |
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Catalogação: | 09/SET/2021 | Língua(s): | ENGLISH - UNITED STATES |
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Tipo: | TEXT | Subtipo: | THESIS | ||||||||||
Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=54602&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=54602&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.54602 | ||||||||||||
Resumo: | |||||||||||||
The ensemble smoother with multiple data assimilation (ES-MDA) gained
much attention as a powerful parameter estimation method. The main idea
of the ES-MDA is to assimilate the same data multiple times with an inflated
data error covariance matrix. In the original ES-MDA implementation, these
inflation factors, such as the number of assimilations, are selected a priori.
The only requirement is that the sum of the inflation factors inverses must be
equal to one. Therefore, selecting them equal to the number of assimilations
is a straightforward choice. Nevertheless, recent studies have shown a relationship
between the ES-MDA update equation and the solution to a regularized
inverse problem. Hence, the inflation factors play the role of the regularization
parameter at each ES-MDA assimilation step. As a result, they have also suggested
new procedures to generate these elements based on the discrepancy
principle. Although several studies proposed efficient techniques to generate
the ES-MDA inflation factors, an optimal procedure to generate them remains
an open problem. Moreover, the studies diverge on which regularization scheme
is sufficient to provide the best ES-MDA outcomes. Therefore, in this work,
we address the problem of generating the ES-MDA inflation factors and their
influence on the method s performance. We present a numerical analysis of
the influence of such factors on the main parameters of the ES-MDA, such
as the ensemble size, the number of assimilations, and the ES-MDA vector of
model parameters update. With the conclusions presented in the aforementioned
analysis, we propose a new procedure to generate ES-MDA inflation
factors based on a regularizing scheme for Levenberg-Marquardt algorithms.
It is shown through a synthetic two-dimensional waterflooding problem that
the new method achieves better model parameters and data match compared
to the other ES-MDA implementations available in the literature.
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