Surface-Wave Extraction Based on Morphological Diversity of Seismic Events
1
School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China
2
The State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China
3
Key Laboratory of Marine Reservoir Evolution and Hydrocarbon Accumulation Mechanism, Ministry of Education, China University of Geosciences (Beijing), Beijing 100083, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(1), 17; https://doi.org/10.3390/app9010017
Received: 14 October 2018 / Revised: 18 December 2018 / Accepted: 19 December 2018 / Published: 21 December 2018
(This article belongs to the Special Issue Seismic Metamaterials)
It is essential to extract high-fidelity surface waves in surface-wave surveys. Because reflections usually interfere with surface waves on X components in multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. To make matters worse, the frequencies and velocities of higher-mode surface waves are close to those of PS-waves. A method for surface-wave extraction is proposed based on the morphological differences between surface waves and reflections. Frequency-domain high-resolution linear Radon transform (LRT) and time-domain high-resolution hyperbolic Radon transform (HRT) are used to represent surface waves and reflections, respectively. Then, a sparse representation problem based on morphological component analysis (MCA) is built and optimally solved to obtain high-fidelity surface waves. An advantage of our method is its ability to extract surface waves when their frequencies and velocities are close to those of reflections. Furthermore, the results of synthetic and field examples confirm that the proposed method can attenuate the distortion of surface-wave dispersive energy caused by reflections, which contributes to extraction of accurate dispersion curves.
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Keywords:
higher-mode surface waves; dispersion curves; morphological component analysis; Radon transform
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MDPI and ACS Style
Qiu, X.; Wang, C.; Lu, J.; Wang, Y. Surface-Wave Extraction Based on Morphological Diversity of Seismic Events. Appl. Sci. 2019, 9, 17.
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