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Dissertação
Estudo comparativo entre estereotomografia e da tomografia da onda NIP: aplicação em dados sintéticos e reais
The determination of an accurate velocity model is a fundamental requirement for the seismic imaging. New methods, such as prestack stereotomography and poststack NIP wave tomography, are powerful and very suggestive tools for this task. The prestack stereotomography is basically based on the con...
Autor principal: | PRAXEDES FILHO, José Ribamar |
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Grau: | Dissertação |
Idioma: | por |
Publicado em: |
Universidade Federal do Pará
2014
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Assuntos: | |
Acesso em linha: |
http://repositorio.ufpa.br/jspui/handle/2011/5760 |
Resumo: |
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The determination of an accurate velocity model is a fundamental requirement for the seismic
imaging. New methods, such as prestack stereotomography and poststack NIP wave tomography,
are powerful and very suggestive tools for this task. The prestack stereotomography is basically
based on the concept of locally coherent events interpreted as primary reflections and that are
associated to ray segments that are linked through the same reflection point in depth. In NIP wave
tomography a seismic event is represented by a hypothetic NIP wave that is associated to a
reflection point in depth. The NIP wave attributes are determined during Common Reflection
Surface (CRS) procedure. The objective of this work is to compare both methods of velocity
model determination in depth. Then a review of the theoretical foundations of both tomographic
methods are made, considering its main differences, and then applied to a synthetic data and a
real marine dataset (seismic line 214-2660 of the Jequitinhonha Basin, Brazil). In order to
evaluate the velocity models determined by these two approximations, the data were prestack
depth migrated using the Kirchhoff algorithm and also generated Common Image Gathers (CIG).
The results have shown that both tomographic methods yield representative velocity models.
However, it was noticed that the velocity model estimated by stereotomography behaved better in
laterally varying media, but only applied in prestack data with a high signal-to-noise ratio. |