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pro vyhledávání: '"da Silva, Sérgio Luiz E. F."'
Time-lapse full-waveform inversion (FWI) has become a powerful tool for characterizing and monitoring subsurface changes in various geophysical applications. However, non-repeatability (NR) issues caused, for instance, by GPS inaccuracies, often make
Externí odkaz:
http://arxiv.org/abs/2407.07467
Autor:
da Silva, Sérgio Luiz E. F., Costa, Felipe T., Karsou, Ammir, de Souza, Adriano, Capuzzo, Felipe, Moreira, Roger M., Lopez, Jorge, Cetale, Marco
We develop a workflow based on full-waveform inversion (FWI) to estimate P-wave velocities in a deepwater Brazilian pre-salt field using the recently introduced circular shot ocean bottom node (OBN) acquisition geometry. Such a geometry comprises a s
Externí odkaz:
http://arxiv.org/abs/2405.17330
Publikováno v:
da Silva & Kaniadakis (2023) Third International Meeting for Applied Geoscience & Energy Expanded Abstracts. pp. 670-674
The statistical basis for conventional full-waveform inversion (FWI) approaches is commonly associated with Gaussian statistics. However, errors are rarely Gaussian in non-linear problems like FWI. In this work, we investigate the portability of a ne
Externí odkaz:
http://arxiv.org/abs/2405.15536
The estimation of physical parameters from data analysis is a crucial point for the description and modeling of many complex systems. Based on R\'enyi $\alpha$-Gaussian distribution and patched Green's function (PGF) techniques, we propose a robust f
Externí odkaz:
http://arxiv.org/abs/2201.12564
Autor:
de Lima, João V. T., da Silva, Sérgio Luiz E. F., de Araújo, João M., Corso, Gilberto, Lima, Gustavo Z. dos Santos
The conventional approach to data-driven inversion framework is based on Gaussian statistics that presents serious difficulties, especially in the presence of outliers in the measurements. In this work, we present maximum likelihood estimators associ
Externí odkaz:
http://arxiv.org/abs/2201.12173
Autor:
da Silva, Sérgio Luiz E. F., Silva, R., Lima, Gustavo Z. dos Santos, de Araújo, João M., Corso, Gilberto
In this work we propose a robust methodology to mitigate the undesirable effects caused by outliers to generate reliable physical models. In this way, we formulate the inverse problems theory in the context of Kaniadakis statistical mechanics (or $\k
Externí odkaz:
http://arxiv.org/abs/2111.09921
Autor:
da Silva, Sérgio Luiz E. F.1,2 (AUTHOR) sergio.dasilva@polito.it, de Araújo, João M.3 (NURSE) gfcorso@gmail.com, de la Barra, Erick4 (AUTHOR), Corso, Gilberto3 (NURSE)
Publikováno v:
Entropy. Jul2023, Vol. 25 Issue 7, p990. 21p.
Autor:
Barbosa, Wagner A.1 (NURSE), da Silva, Sérgio Luiz E. F.2,3 (AUTHOR) sergioluizsilva@id.uff.br, de la Barra, Erick4,5 (AUTHOR), de Araújo, João M.1 (NURSE)
Publikováno v:
PLoS ONE. 11/11/2022, Vol. 17 Issue 11, p1-27. 27p.
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