none 10.1190/geo2020-0002.1 Society of Exploration Geophysicists Society of Exploration Geophysicists 186 121515933 5981 2026041615245963100 10.1190 2026-04-16T19:25:15Z 2020-11-24T10:37:33Z 12 Geophysics 0016-8033 1942-2156 03 01 2021 86 2 Maher Nasr Institut National de la Recherche Scientifique 1 , Centre Eau Terre Environnement, 490 rue de la Couronne, Québec, (Québec) G1K 9A9, Canada. E-mail: maher.nasr@ete.inrs.ca (corresponding author); bernard.giroux@ete.inrs.ca . http://orcid.org/0000-0003-4321-4319 Bernard Giroux Institut National de la Recherche Scientifique 1 , Centre Eau Terre Environnement, 490 rue de la Couronne, Québec, (Québec) G1K 9A9, Canada. E-mail: maher.nasr@ete.inrs.ca (corresponding author); bernard.giroux@ete.inrs.ca . http://orcid.org/0000-0002-2042-2759 J. Christian Dupuis Université Laval 2 , Département de Géologie et de Génie Géologie, Quebec G1V 0A6, Canada. E-mail: christian.dupuis@ggl.ulaval.ca . ABSTRACT Polarization filters (PFs) are widely used for denoising seismic data. These filters are applied in the fields of seismology, microseismic monitoring, vertical seismic profiling, and subsurface imaging. They are primarily useful to suppress ground roll in seismic reflection data and enhance P- and S-wave arrivals. Traditional implementations of PFs involved the analysis of the covariance matrix or the singular value decomposition (SVD) of a 3C seismogram matrix. The linear polarization level, known as rectilinearity, is expressed as a function of the covariance matrix eigenvalues or by the data matrix singular values. Wavefield records that are linearly polarized are amplified, whereas others are attenuated. Besides the described implementations, we have developed a new time-domain PF based on the analysis of the seismic data correlation matrix. The principal idea is to extend the notion of the correlation coefficient in 3D space. This new filter avoids the need for diagonalization of the covariance matrix or SVD of data matrix, which are often time-consuming. The new implementation facilitates the choice of the rectilinearity threshold: We determine that linear polarization in three dimensions can be represented as three classic 2D correlations. A good linear polarization is detected when a high linear correlation between the three seismogram components is mutually observed. The tuning parameters of the new filter are the length of the time window, the filter order, and the rectilinearity threshold. Tests using synthetic seismograms indicate that optimal results are reached with a filter order that spans between 2 and 4, a rectilinearity threshold between 0.3 and 0.7, and a window length that is equivalent to one to three times the period of the signal wavelet. Compared with covariance-based filters, the new filter can enhance the signal-to-noise ratio by 6–20 dB and reduces computational costs by 25%. 02 05 2021 03 01 2021 V91 V106 Fonds de Recherche du Québec - Nature et Technologies http://dx.doi.org/10.13039/501100003151 Bernard Giroux ArcelorMittal http://dx.doi.org/10.13039/501100002734 Bernard Giroux 1 10.1190/crossmark-policy library.seg.org true 2020-01-02 2020-10-28 2020-10-29 2021-02-05 Fonds de Recherche du Québec - Nature et Technologies http://dx.doi.org/10.13039/501100003151 Bernard Giroux ArcelorMittal http://dx.doi.org/10.13039/501100002734 Bernard Giroux 10.1190/geo2020-0002.1 https://pubs.geoscienceworld.org/geophysics/article/86/2/V91/594570/A-novel-time-domain-polarization-filter-based-on-a https://pubs.geoscienceworld.org/seg/geophysics/article-pdf/86/2/V91/5258275/geo-2020-0002.1.pdf https://pubs.geoscienceworld.org/seg/geophysics/article-pdf/86/2/V91/5258275/geo-2020-0002.1.pdf https://pubs.geoscienceworld.org/geophysics/article/86/2/v91/594570/a-novel-time-domain-polarization-filter-based-on-a 0016-8025 Geophysical Prospecting Akram 66 872 2018 10.1111/1365-2478.12597 An application of waveform denoising for microseismic data using polarization-linearity and time-frequency thresholding 0037-1106 Bulletin of the Seismological Society of America Amoroso 102 854 2012 10.1785/0120110140 S-wave identification by polarization filtering and waveform coherence analyses Computers & Geosciences Bohlen 28 887 2002 10.1016/S0098-3004(02)00006-7 Parallel 3-D viscoelastic finite difference seismic modelling Food Quality and Preference Borgognone 12 323 2001 10.1016/S0950-3293(01)00017-9 Principal component analysis in sensory analysis: Covariance or correlation matrix? 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