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Estatística
Título: LAWIE: SPARSE-SPIKE DECONVOLUTION WITH LASSO AND WIENER FILTER
Autor: FELIPE JORDAO PINHEIRO DE ANDRADE
Colaborador(es): MARCELO GATTASS - Orientador
Catalogação: 06/NOV/2020 Língua(s): PORTUGUESE - BRAZIL
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.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=50236&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=50236&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.50236
Resumo:
This work proposes an algorithm for solving the seismic sparse-spike deconvolution problem. Entitled LaWie, this algorithm is based on the combination of Least Absolute Shrinkage and Selection Operator (LASSO) and the block modeling used in the Wiener filter. Deconvolution is done trace by trace to estimate the reflectivity profile and the convolution wavelet that originated the seismic amplitudes. This work presents the results in the synthetic dataset of Marmousi2, where there is a ground truth for objective comparisons. Also, this work presents the results in a real dataset, Netherlands Offshore F3 Block, and shows the applicability of the proposed algorithm to outline the reflectivity profile and highlight characteristics such as fractures in this data.
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