Double projection three‐component groundroll filter

Becquey, M.; Rodriguez, Salvador García

doi:10.1190/1.1815860

Cited by 2 publications

(2 citation statements)

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“…To remove ground roll, Becquey and Manin () presented an ellipticity filter using discrete wavelet transforms on each component. Becquey and Rodriguez () used spectral matrix filtering to select linear polarization events. Picheral et al () proposed a shift invariance method to estimate apparent velocity and polarization jointly.…”

Section: Some Signal Processing Tools For Surface‐wave Estimationmentioning

confidence: 99%

Advanced signal processing tools for dispersive waves

Mars¹,

Glangeaud²,

Mari

2004

Near Surface Geophysics

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Two field examples are presented, showing the advantages of using multicomponent sensors for surface-wave studies. Multicomponent sensors allow the use of specific signal-processing tools such as the multicomponent singular value decomposition filter and the multicomponent polarization filter, which are both very efficient at separating surface waves from the other waves that comprise a seismic field record.Firstly, some signal-processing tools for studying surface waves are described. The various filters range from classical to advanced techniques. For processing single-component data, the filters are the f-k filter and filters based on singular value decomposition and on spectral matrix decomposition. For processing multicomponent data, the filters are the 4C-singular value decomposition filter and the classical or high-order polarization filter.Secondly, processing sequences that can be applied to the field data are described and the single-component processing sequence and the multicomponent processing sequence are compared.Two field examples are presented. The first data set is a land seismic data recording on 2C sensors. The second data set was obtained from a marine acquisition with OBS (4 components). The results obtained illustrate the advantages of using multicomponent filters. The efficiency of the 4C-SVD filter and the high-order statistic polarization filter is demonstrated. sedimentary layer and of the parameters of dispersion is used to determine the constraints for modelling the propagation environment Nicolas et al. 2003).The analysis of surface waves and the study of their dispersion allow us to evaluate the shear-wave velocity as a function of depth and to determine the shear modulus of the first tens of metres below the ground surface. For any recording, we need a source and at least two geophones. The source can be impulsive, i.e. hammer-type, or it can have a single frequency at every shot. Useful frequencies for the determination of the pseudo-Rayleigh velocity vary from 3 to 200 Hz. Surveys are often carried out over the frequency range from 10 to 100 Hz (Matthews et al., 1996). Six or more geophones are used with a spacing of 1, 2, 3 or 4 m for accurate measurements of phase differences. This allows a phase velocity versus wavelength diagram to be computed. The measurement of phase is carried out in the frequency domain after a Fourier transform of traces recorded by the geophones. When a vibrator is used, one trace is obtained per frequency emitted, the frequency being that for which the amplitude spectrum is maximal. With an impulsive source, phases are measured in the frequency zone corresponding to the maximum of the amplitude spectrum and the coherence function. In this approach, we assume that the surface waves are dominant and the effects of the other waves are negligible. Once the phase velocity versus wavelength diagram is obtained, an inversion process is used to trans-* Jerome.Mars@lis.inpg.fr

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Section: Some Signal Processing Tools For Surface‐wave Estimationmentioning

confidence: 99%

Advanced signal processing tools for dispersive waves

Mars¹,

Glangeaud²,

Mari

2004

Near Surface Geophysics

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“…The double projection filter (Becquey and Rodriguez, 2000) estimates the local polarisation and apparent velocity of the ground roll in the frequency band where it predominates and projects the data onto these vectors. Adding polarisation to velocity as filtering parameters, it requires multicomponent data.…”

Section: Velocity and Polarisation: Double Projection Filtermentioning

confidence: 99%

Surface wave attenuation in foothills areas: two innovative approaches

Duval¹,

Ancel²,

Becquey³

et al. 2005

SEG Technical Program Expanded Abstracts 2005

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SummarySurface wave attenuation is a difficult problem to address in foothills areas due to the high variability of their typology. Such recorded events can indeed be non linear and even mimic reflection hyperbolas.We present two innovative approaches that exploit the combination of different criteria so as to discriminate between effective signal and noise. The first one makes use of both apparent velocity and polarisation. Its ability to detect noise is demonstrated on a synthetic multi-component data set inspired from South American foothills. The second one combines apparent velocity and a decomposition on different time and space scales. Improvements over classical FK filtering are shown on a single component real data set from Canadian foothills.

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Double projection three‐component groundroll filter

Cited by 2 publications

References 1 publication

Advanced signal processing tools for dispersive waves

Advanced signal processing tools for dispersive waves

Surface wave attenuation in foothills areas: two innovative approaches

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