Data‐matrix asymmetry and polarization changes from multicomponent surface seismics

Li, Xiangyang; MacBeth, Colin

doi:10.1190/1.1444171

Cited by 12 publications

(4 citation statements)

References 15 publications

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“…Besides, compensating multicomponent data for acquisition-related perturbations is important because these distort the characteristics of the vector wavefield; coupling has a different effect on horizontal and vertical receiver components (Krohn, 1984). This coupling can bias the observed polarization (Li and MacBeth, 1997;Michaud and Snieder, 2004). For example, determining the polarization direction of the leading split shear wave involves simultaneous rotation of the horizontal source and receiver coordinates to conform with the principal axes of an azimuthally anisotropic medium (Alford, 1986).…”

Section: Discussionmentioning

confidence: 99%

Surface-consistent deconvolution using reciprocity and waveform inversion

et al. 2006

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Source and receiver responses must be equalized when their behavior or coupling changes with location within a given survey. Existing surface-consistent deconvolution techniques that account for these effects assume that common-midpoint (CMP) gathering is valid-the seismic trace is decomposed into a source function, a receiver response, a normal-incidence reflectivity term, and an offsetrelated component that is laterally shift invariant. As a result, the performance of existing surface-consistent deconvolution techniques is best when applied to primary reflection data only, since the offset dependency of ground roll and multiples varies laterally in media with lateral variations. We have developed an alternative method for surfaceconsistent deconvolution that is applicable to the entire seismic trace and is therefore essentially a raw-data preprocessing step. The method is based on reciprocity of the medium response. Assuming that conditions for applicability of reciprocity are met, we can attribute differences between normal and reciprocal recordings to the source and receiver perturbations. Contrary to existing surface-consistent deconvolution methods, this approach uses the full description of the wavefield and is therefore ideally suited for prestack processing. We have applied this technique to single-sensor data acquired in Manistee County, Michigan. At this site, nearsurface conditions vary, and this significantly affects data quality. The application of the new deconvolution procedure substantially improves S/N ratio on both prestack and poststack data, and these results compare favorably to those obtained using existing surface-consistent deconvolution techniques, since they require subjective data scaling to obtain acceptable results. The obtained source corrections are correlated to changes in near-surface conditions-in this case, to changes in water-saturation levels. We do not observe such a correlation for the receiver corrections, which vary rapidly along the spread. Finally, the receiver response does not agree with the generally accepted damped harmonic oscillator model. For frequencies below 100 Hz, the retrieved receiver variations are larger than predicted by this model, and we cannot explain the receiver response using a single resonant frequency for the geophone-ground coupling. V19 V20 van Vossen et al.

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Section: Discussionmentioning

confidence: 99%

Surface-consistent deconvolution using reciprocity and waveform inversion

et al. 2006

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“…For multicomponent data, it is important to realize that acquisition‐related perturbations distort the vector‐wavefield characteristics, since coupling has a different effect on horizontal and vertical source and receiver components (Krohn 1984). This can bias the observed polarization (Li & MacBeth 1997; Michaud & Snieder 2004). For example, determining the polarization direction of the leading split shear wave involves simultaneous rotation of the horizontal source and receiver coordinates to conform with the principal axes of an azimuthal anisotropic medium (Alford 1986).…”

Section: Introductionmentioning

confidence: 99%

Surface-consistent amplitude corrections for single or multicomponent sources and receivers using reciprocity and waveform inversion

Vossen¹,

Curtis

Trampert³

2006

Geophysical Journal International

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S U M M A R YIn land seismics, near-surface conditions often vary within surveys, resulting in differences in source strength and signature. Furthermore, discrepancies between closely spaced recordings are also commonly observed. Processing and interpretation of recorded data require that data are corrected for these source and receiver perturbations in the early stages of processing. However, existing surface-consistent deconvolution techniques are applicable to primary reflection data only, and therefore require that ground roll and multiples are suppressed prior to the application. This is usually performed with multichannel filter operations. The performance of these filter operations, however, rapidly deteriorates in presence of acquisition-related amplitude and phase perturbations. We propose an alternative approach to compensate for acquisition-related amplitude perturbations, which has the advantage of being purely a pre-processing step. It has the following characteristics: (i) it can be applied to complete recordings, hence does not require the isolation of primary reflections in the data, (ii) no assumptions are imposed on the subsurface and (iii) it is applicable to multicomponent data. The procedure is based on reciprocity of the medium response, so that differences between normal and reciprocal traces can be attributed to source and receiver perturbations. The application of reciprocity requires symmetric data acquisition, that is, identical source and receiver patterns, identical locations, and the source orientations have to be identical to the receiver components. Besides reciprocity, additional constraints are required to determine the lateral source and receiver amplitude variations fully. We use criteria based on minimizing total energy differences between adjacent common source and common receiver gathers, and in common offset panels of the medium response. Synthetic tests demonstrate that acquisition-related amplitude differences can be significantly reduced using this method.

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“…However, the off-diagonal (residual) components might not be eliminated. Although they are usually smaller than the diagonals (Li and MacBeth, 1997), they do have some effects on the processing. We refer this residual energy in the offdiagonal components after the initial rotation as the residual wavefield.…”

Section: Introductionmentioning

confidence: 99%

“…However, depth change of polarization may be common, particularly, in fractured reservoirs. Wintersten and Meadows (1991), and Thomsen et al (1995), and Li and MacBeth (1997) have presented methods to recover the polarization change. Most of these methods are based on layer-stripping, and they are not applicable to surface data when the polarization change do not associated with an impedance change.…”

Section: Introductionmentioning

confidence: 99%

Interpreting the residual wavefield for polarization change in a 4‐C shear‐wave data matrix

Dai¹,

Li²

1998

SEG Technical Program Expanded Abstracts 1998

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Multicomponent shear-wave data recorded at an oblique line-azimuth to the natural coordinate system will display shear-wave splitting (birefringence). After the initial rotation into the natural coordinate system, there is often still significant residual energy left in the off-diagonal components of the 4-C shear-wave data matrix, and these signals, referred to as the residual wavefields, are often ignored in subsequent processing. This work investigates the link between the residual wavefield and polarization changes in a 4-C shear-wave data matrix. Local polarization changes cause local scattering, and the energy in the off-diagonals cannot be eliminated by rotation with an average polarization angle. It is consequently possible to detect the polarization change by analysing the residual wavefield. This is achieved by extracting the instantaneous polarization using a singular value decomposition of the 4-C data matrix into principal and residual components. Both synthetic and real data will be used to illustrate the scheme.

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Data‐matrix asymmetry and polarization changes from multicomponent surface seismics

Cited by 12 publications

References 15 publications

Surface-consistent deconvolution using reciprocity and waveform inversion

Surface-consistent deconvolution using reciprocity and waveform inversion

Surface-consistent amplitude corrections for single or multicomponent sources and receivers using reciprocity and waveform inversion

Interpreting the residual wavefield for polarization change in a 4‐C shear‐wave data matrix

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