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Volume 68, Issue 7
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Obtaining geological information from seismic data motivates researchers to innovate and improve seismic wave processing tools. Polarization‐based methods have received much attention regarding their ability to discriminate between different phases of the seismic wave based on polarity. Combining the intuitive definition of polarity in the frequency domain (monochromatic waves) with the non‐stationary properties provided by time‐domain methods, time‐frequency approaches are attracting widespread interest because they localize the information extracted from the seismic waves in the joint time and frequency domains. Due to the lack of high‐resolution time‐frequency maps, the time‐frequency polarization approach was not able to resolve specific temporal polarity changes in the seismic signal. The main objective of this study was to devise a robust time‐frequency‐based polarization filtering method using high‐resolution polarization attributes obtained directly from the sparse time‐frequency map without using Eigen analysis or analytic signals. The method proposed here utilizes a computationally effective sparsity‐based adaptive S‐transform to obtain a high‐resolution polarization map of an inherently non‐stationary seismogram for the entire frequency content of the signal at different times. The superiority of the proposed method over the S‐transform method was verified using synthetic and real data sets to calculate the polarization attributes in the time‐frequency domain and separate the Rayleigh waves from the seismogram.

© 2020 European Association of Geoscientists & Engineers © 2020 European Association of Geoscientists & Engineers
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/content/journals/10.1111/1365-2478.12994
2020-07-03
2024-04-25

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Rayleigh wave separation using high‐resolution time‐frequency polarization filter
Geophysical Prospecting 68, 2104 (2020); https://doi.org/10.1111/1365-2478.12994
/content/journals/10.1111/1365-2478.12994
/content/journals/10.1111/1365-2478.12994
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  • Article Type: Research Article
Keyword(s): Rayleigh wave separation; Sparsity‐based adaptive S‐transform; Time‐frequency‐based polarization analysis

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