Dip selective 2-D multiple attenuation in the plane‐wave domain

Liu, Faqi; Sen, Mrinal K.; Stoffa, Paul L.

doi:10.1190/1.1444717

Cited by 17 publications

(7 citation statements)

References 14 publications

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“…This mapping is also applicable to refraction geometry used in the recent work of supervirtual interferometry (Mallison et al, 2011;Bharadwaj et al, 2012). Numerous methods using this transform have been investigated for seismic wave filtering (Tatham, 1989), multiple attenuation (Liu et al, 2000), seismic forward modeling (Vigh and Starr, 2008;Tao and Sen, 2013a), migration (Stoffa et al, 2006), and inversion (Sen et al, 2003).…”

Section: Introductionmentioning

confidence: 89%

On a plane-wave based crosscorrelation-type seismic interferometry

Tao

Sen

2013

GEOPHYSICS

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We explored a new approach to retrieve virtual seismic responses from crosscorrelating acquired seismic data in the plane-wave domain. Using this method, slant stacking is first performed over shot or receiver locations of observed seismic data to produce plane-wave transformed gathers. Crosscorrelation is then performed by selecting traces with the same ray parameters from different shot or receiver locations of the plane-wave gathers. Unlike traditional crosscorrelation-type time-space domain interferometry, where full range of ray parameters is used for each survey location, this method directly selects common ray parameters to cancel overlapping raypaths. This approach can be used to retrieve reflections in the presence of dispersive waves and to select certain ranges of ray parameters with directional wave paths for retrieval. It can avoid spurious arrivals in supervirtual interferometry when unwanted arrivals such as reflections break the requirement of conventional interferometry. In addition, computation time can be saved with this approach because plane-wave transform usually results in a reduction of the original data volume. We demonstrate this method with synthetic and ocean bottom seismometer data examples.

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Section: Introductionmentioning

confidence: 89%

On a plane-wave based crosscorrelation-type seismic interferometry

Tao

Sen

2013

GEOPHYSICS

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“…From Liu et al (2000), seismic data with multiples can be described in the p-ω domain using the following equation:…”

Section: Theory and Methodsmentioning

confidence: 99%

“…Traditionally, this inversion is carried out in x-ω domain. Liu et al (2000) extended this method to the 2D problems in the plane wave domain. In this case, matrix inversion can be carried out in k-ω domain by a scalar inversion resulting in a very fast algorithm (Berkhout and Verschuur, 2006).…”

Section: Introductionmentioning

confidence: 99%

Multiple attenuation using inverse data processing in the plane‐wave domain

Sen

Chen

2008

SEG Technical Program Expanded Abstracts 2008

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We propose an inverse data processing method in the plane wave domain for free surface multiple attenuation. Traditionally, inverse data processing is carried out using data matrix in space-frequency (x-ω) domain (Berkhout, 2006). For flat-lying layers, the data matrix will have a Toeplitz structure, which means that the inversion can be carried out in frequency wave-number (k-ω) domain. Here we propose an alternate method of implementing the inversion in a coupled plane-wave domain where the bandwidth of the matrix can be chosen based on the dominant dip resulting in a stable and fast algorithm.

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“…Berkhout (2006), Kelamis et al (2006), and Berkhout and Verschuur (2007a, b) use an inverse data space approach. Liu et al (2000) predict multiples using coupling of slownesses (p-values), but information about the source wavelet and reflector dips is still required. Wavefront curvature and emergence angles are used by Landa et al (1999b) and Keydar et al (1998) to predict multiples.…”

Section: Introductionmentioning

confidence: 99%

Data-driven, target-oriented, kinematic prediction and subtraction of multiples from pure and mode-converted multicomponent data

Cao

McMechan

2011

GEOPHYSICS

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Most multiple removal algorithms focus on multiples of primary P-wave reflections; removal of multiples of converted reflections have not received comparable attention, so explicit consideration is overdue. A target-oriented algorithm predicts converted wave multiples by coupling apparent slownesses, and then subtracts them from elastic common-source data in a data-adaptive window. Prediction is based on matching apparent slownesses in common-source and common-receiver gathers at all source and receiver locations along the propagation path. Predictions use only offset and traveltime, of the primary pure and converted waves that produce the multiples, picked from common-source gathers, and the slownesses calculated from them. Higher-order multiples can be predicted by repeating this process to match slownesses at a sequence of alternating source and receiver locations in turn. Primary reflections (e.g., SS, SP, and PS) that are considered to be noise, can also be subtracted.The predictions are data-driven and require no velocities, angles, reflector orientations or free-surface topography. Any single component (usually vertical) may be used to identify and pick the traveltimes. The resulting predictions are also valid for all other components. The subtraction involves flattening the predicted time trajectory of the multiple, followed by trace averaging to estimate the local wavelet at each location in a moving trace and time window that contains the wavelet of the multiple. The subtraction is data-adaptive, and implicitly involves amplitude and phase information, so separate or prior estimation of the source time or directivity functions is not required. Two synthetic examples showed that the slowness-based algorithm is successful in predicting and reducing converted wave multiples in an elastic medium. Migrated P-wave subsurface images are generated before and after multiple removal to evaluate the performance. Polarity correction of the horizontal component (either before or after subtraction) ensures coherent stacking.

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Dip selective 2-D multiple attenuation in the plane‐wave domain

Cited by 17 publications

References 14 publications

On a plane-wave based crosscorrelation-type seismic interferometry

On a plane-wave based crosscorrelation-type seismic interferometry

Multiple attenuation using inverse data processing in the plane‐wave domain

Data-driven, target-oriented, kinematic prediction and subtraction of multiples from pure and mode-converted multicomponent data

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