Preprint Article Version 2 This version is not peer-reviewed

Surface-Wave Extraction Based on Morphological Diversity of Seismic Events

Version 1 : Received: 14 October 2018 / Approved: 16 October 2018 / Online: 16 October 2018 (11:31:18 CEST)
Version 2 : Received: 16 October 2018 / Approved: 17 October 2018 / Online: 17 October 2018 (09:00:53 CEST)

A peer-reviewed article of this Preprint also exists.

Qiu, X.; Wang, C.; Lu, J.; Wang, Y. Surface-Wave Extraction Based on Morphological Diversity of Seismic Events. Appl. Sci. 2019, 9, 17. Qiu, X.; Wang, C.; Lu, J.; Wang, Y. Surface-Wave Extraction Based on Morphological Diversity of Seismic Events. Appl. Sci. 2019, 9, 17.

Journal reference: Appl. Sci. 2018, 9, 17
DOI: 10.3390/app9010017

Abstract

Extraction of high-resolution surface waves is essential in surface-wave survey. Because reflections usually interfere with surface waves on X component in a multicomponent seismic exploration, it is difficult to extract dispersion curves of surface waves. The situation goes more serious when 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 reflections and surface waves. 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, the sparse representation problem based on the 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, 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 extracting accurate dispersion curves.

Subject Areas

higher-mode surface waves; dispersion curves; morphological component analysis; Radon transform

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