Critical angle of reflections and Poisson's ratio from spectral recomposition

被引:6
|
作者
Zuniga, Nelson Ricardo Coelho Flores [1 ,2 ,4 ]
Draganov, Deyan [3 ]
Ghose, Ranajit [3 ]
机构
[1] Univ Sao Paulo IAG USP, Dept Geophys, Inst Astron Geofis & Ciencias Atmosfer, Rua Matao 1226 Cidade Univ, BR-05508090 Sao Paulo, SP, Brazil
[2] Univ Sao Paulo POLI USP, Dept Min & Petr Engn, Escola Politecn, Ave Pro Luciano Gualberto 380, Cidade Univ, BR-05508010 Sao Paulo, SP, Brazil
[3] Delft Univ Technol, Fac Civil Engn & Geosci, Stevinweg 1, NL-2628 CN Delft, Netherlands
[4] Univ Sao Paulo IAG USP, Inst Astron Geofis & Ciencias Atmosfer, Rua Matao 1226 Cidade Univ, BR-05508090 Sao Paulo, SP, Brazil
关键词
Critical angle; Poisson's ratio; Spectral recomposition; Inversion; Frequency spectrum; SEISMIC VELOCITIES;
D O I
10.1016/j.jappgeo.2023.105110
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Using the critical angle information of a reflection event, it is possible to calculate several essential physical parameters that are key to reliable geological characterization of the subsurface. However, estimation of the critical angle usually requires several steps of seismic processing. For this reason, an approach which is capable of estimating the critical angle directly from the data is of interest. Once the critical angle is estimated, it is possible to estimate further the Poisson's ratio and the seismic velocities. In this work, we propose an approach which can perform this estimation, based on spectral recomposition of seismic data. We design an inversion scheme in order to reconstruct the seismic spectrum of wavelets of a reflection event, which subsequently allows us to estimate the critical angle of near-surface reflection events without performing prior velocity analysis. After finding the critical angle, we show next how to estimate the Poisson's ratio and the compressional-and shear-wave velocities of the medium above the reflector. The approach leads to quite accurate values for Poisson's ratio even for noisy data, in case the number of layers is not large.
引用
收藏
页数:14
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