Seismic Velocity and Polarization Estimation for Wavefield Separation

Donno, Daniela; Nehorai, Arye; Spagnolini, Umberto

doi:10.1109/tsp.2008.927459

Cited by 26 publications

(13 citation statements)

References 38 publications

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“…Since wave propagation properties are related to time, frequency, and wavenumber (Donno et al, 2008), TFK transform provides a more comprehensive view to identify wave-field and recover the polarization attributes, especially when dispersive surface waves exist. Based on TFK transform, we proposed a two-step polarization workflow, non-stationary filtering followed by time-frequency-wavenumber dependent polarization analysis.…”

Section: Methodsmentioning

confidence: 99%

A New Method of Surface Wave Analysis and OBC Signal Enhancement in Shallow Water Environment of the Arabian Gulf using Time-Frequency-Wavenumber Polarization Analysis

Zhang

Sun

Berteussen³

et al. 2014

Abu Dhabi International Petroleum Exhibition and Conference

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In the shallow water environment of the Arabian Gulf, a combination of strong lateral seafloor heterogeneities, shallow water depths (~10m), and hard sea bottom results in highly dispersive and aliased surface waves with complex wave-field polarization in all four components of the OBC seismic data. Compared to body waves, surface waves are characterized by low velocity, low frequency and high polarization and their polarization states are time, frequency and mode dependent. Those properties challenge the existing surface waves filtering techniques because they take into account velocity, frequency or polarization only. Consequently, the residual surface wave leads to inaccurate directional analysis and has severe adverse effect on the quality of subsequent seismic data processing algorithms.Considering the joint relationship among wavenumber, time, frequency and polarization of surface waves, we propose a two-step rotation method to separate the surface waves from the reflected waves and estimate wave polarizations. First, we use a non-stationary FK filter to eliminate the effect of the surface wave from OBC record in the time-frequency-wavenumber (TFK) domain, where we can define the surface wave rejection zone by its low frequency, low velocity and high amplitude characteristics. Second, considering the pattern of particle motion and propagation directions, we estimate wave-field polarization features by extending the traditional single domain polarization analysis into the decomposed TFK domain. Spherically polarization noises (surface waves) can be distinguished from rectilinearly polarized waves (body waves) through covariance matrix calculation for each TFK point. Therefore, the residual surface wave which overlaps with body waves in TFK domain are eliminated based on its polarization characteristic. Analysis on field data shows that this proposed new method is effective in both attenuating the surface waves and providing reliable information on orientation, which are critical for the further processing on the shear wave and converted wave in horizontal components.

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Section: Methodsmentioning

confidence: 99%

A New Method of Surface Wave Analysis and OBC Signal Enhancement in Shallow Water Environment of the Arabian Gulf using Time-Frequency-Wavenumber Polarization Analysis

Zhang

Sun

Berteussen³

et al. 2014

Abu Dhabi International Petroleum Exhibition and Conference

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show abstract

“…The tensor approach through CP decomposition fully takes advantage of the multilinearity of a model with at least three diversities [9]. However, in order to have a totally multilinear model in (13), we need to remove the dependency on ω q from factor matrices A and B, e.g. through a bilinear interpolation.…”

Section: Space Shift and Polarization Togethermentioning

confidence: 99%

“…Another element of diversity is given by wave polarization, whenever each sensor has multiple components, i.e. it records particle displacement along three perpendicular directions [10], [11], [12], [13]. The above mentioned tensor approach of [8] was extended to include polarization diversity in [14], [15], [16], and propagation speed diversity of seismic waves F. E. D. Raimondi, P. Comon and O. J. Michel are with GIPSA-Lab, CNRS, Univ.…”

Section: Introductionmentioning

confidence: 99%

Wideband Multiple Diversity Tensor Array Processing

Raimondi

Farias

Michel

et al. 2017

IEEE Trans. Signal Process.

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“…For instance, in vertically-heterogeneous media, Rayleigh waves (a type of surface waves characterised by elliptical polarisation in the vertical plane defined by the direction of motion of the wave), may be distinguished from Love waves (another type of surface waves whose polarisation is linear in the transverse-horizontal direction) and pressure and shear waves (body waves characterised by linear polarisation). Moreover, in the literature, several publications show applications of data-filtering and wavefieldseparation techniques based on the polarisation information [5,6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Characterisation and extraction of a Rayleigh-wave mode in vertically heterogeneous media using quaternion SVD

Sajeva

Menanno

2017

Signal Processing

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We propose a method that identifies a mode of Rayleigh waves and separates it from body waves and from other modes, using quaternions to represent multi-component data. Being well known the abilities of quaternions to handle rotations in space, we use previous results derived from Le Bihan and Mars (2004) to prove that a Rayleigh-wave mode recorded by an array of vector-sensors can be approximated by a sum of trace-by-trace rotating time signals. Our method decomposes the signal into narrow-frequency bands, which undergo both a velocity correction and a polarisation correction. The aim of these corrections is to reduce the mode of interest to a quasi-monochromatic wave packet with infinite apparent velocity and quasi-circular polarisation. Once written in quaternion notation, we refer to this wave packet as quaternion brick. Based on theoretical considerations, we prove that this quaternion brick maps into the first quaternion eigenimage of the quaternion singular value decomposition. We apply this method to synthetic datasets derived from two vertically heterogeneous models to extract the fundamental mode and we prove that it is correctly separated from either a higher mode of propagation or body waves with negligible residual. Results are presented in both time-offset and frequency-phase slowness domains

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Seismic Velocity and Polarization Estimation for Wavefield Separation

Cited by 26 publications

References 38 publications

A New Method of Surface Wave Analysis and OBC Signal Enhancement in Shallow Water Environment of the Arabian Gulf using Time-Frequency-Wavenumber Polarization Analysis

A New Method of Surface Wave Analysis and OBC Signal Enhancement in Shallow Water Environment of the Arabian Gulf using Time-Frequency-Wavenumber Polarization Analysis

Wideband Multiple Diversity Tensor Array Processing

Characterisation and extraction of a Rayleigh-wave mode in vertically heterogeneous media using quaternion SVD

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