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Tese
Seismic amplitude analysis and quality factor estimation based on redatuming
Amplitude correction is an important task to correct the seismic energy dissipated due the ineslasticity absortion and the geometrical spreading during the acoustic/elastic wave propagation in solids. In this work, we propose a way to improve the estimation of quality factor from seismic reflection...
Autor principal: | OLIVEIRA, Francisco de Souza |
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Grau: | Tese |
Idioma: | eng |
Publicado em: |
Universidade Federal do Pará
2019
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Assuntos: | |
Acesso em linha: |
http://repositorio.ufpa.br/jspui/handle/2011/11377 |
Resumo: |
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Amplitude correction is an important task to correct the seismic energy dissipated due the ineslasticity absortion and the geometrical spreading during the acoustic/elastic wave propagation in solids. In this work, we propose a way to improve the estimation of quality factor from seismic reflection data, with a methodology to estimate de quality factor based on the combination of the peak frequency-shift (PFS) method and the redatuming operator. The innovation in this work is in the way we correct travel times when the medium is consisted by many layers. In other words, the correction of traveltime table used in the PFS method is performed using the redatuming operator. This operation, which is performed iteratively, allows to estimate the Q-factor layer by layer in a more accurate way. A redatuming operation is used to simulate the acquisition of data in new levels, avoiding distortions produced by near-surface irregularities related to either geometric or material property heterogeneities. In this work, the application of the true-amplitude Kirchhoff redatuming (TAKR) operator on homogeneous media is compared
with conventional Kirchhoff redatuming (KR) operator restricted to the zero-offset case. Our methodology is based on the combination of the peak frequency-shift (PFS) method and the redatuming operator (TAKR with weight equal 1). Application in synthetic and in seismic (Viking Graben) and GPR (Siple Dome) real data demonstrates the feasibility of our analysis. |