Source signature estimation based on the removal of first‐order multiples

Ikelle, Luc T.; Roberts, Gareth; Weglein, Arthur B.

doi:10.1190/1.1444291

Cited by 46 publications

(20 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…During the second stage, measures are taken to compensate for imperfections in the multiple predictions. For SRME, predicted multiples often include source signatures and directivity patterns that differ from those present in the data ͑see, e.g., Verschuur et al, 1992;Ikelle et al, 1997͒. Moreover, 2D SRME produces errors in the predicted multiples because of 3D complexity of the earth ͑Dragoset and Jeričević, 1998; Ross et al, 1999;Verschuur, 2006͒, whereas recently developed full 3D-SRME algorithms can suffer from imperfections related to incomplete acquisitions ͑see, e.g., Lin et al, 2004;Moore and Dragoset, 2004;van Borselen et al, 2004;van Dedem and Verschuur, 2005͒, including erroneous reconstructions of missing near offsets ͑Dragoset and Jeričević, 1998͒.…”

Section: Introductionmentioning

confidence: 99%

Adaptive curvelet-domain primary-multiple separation

2008

View full text Add to dashboard Cite

In many exploration areas, successful separation of primaries and multiples greatly determines the quality of seismic imaging. Despite major advances made by surface-related multiple elimination ͑SRME͒, amplitude errors in the predicted multiples remain a problem. When these errors vary for each type of multiple in different ways ͑as a function of offset, time, and dip͒, they pose a serious challenge for conventional least-squares matching and for the recently introduced separation by curvelet-domain thresholding. We propose a data-adaptive method that corrects amplitude errors, which vary smoothly as a function of location, scale ͑fre-quency band͒, and angle. With this method, the amplitudes can be corrected by an elementwise curvelet-domain scaling of the predicted multiples. We show that this scaling leads to successful estimation of primaries, despite amplitude, sign, timing, and phase errors in the predicted multiples. Our results on synthetic and real data show distinct improvements over conventional least-squares matching in terms of better suppression of multiple energy and high-frequency clutter and better recovery of estimated primaries.

show abstract

Section: Introductionmentioning

confidence: 99%

Adaptive curvelet-domain primary-multiple separation

2008

View full text Add to dashboard Cite

show abstract

“…The current multiple attenuation methods for surface seismic data (e.g. Carvalho, Weglein and Stolt 1991; Verschuur, Berkhout and Wapenaar 1992; Dragoset 1994; Menger, Marek and Heinze 1996; Ikelle, Roberts and Weglein 1997; Weglein et al . 1997) take the view that the direct wave must be muted as a prerequisite step to the multiple attenuation process and that receiver ghost events can be treated as part of an effective source signature.…”

Section: Introductionmentioning

confidence: 99%

Combining two seismic experiments to attenuate free‐surface multiples in OBC data*

Ikelle

1999

Geophysical Prospecting

Self Cite

View full text Add to dashboard Cite

The current inverse scattering solution used for multiple attenuation of marine seismic reflection data assumes that sources and receivers are located in the water. To adapt this solution to the ocean-bottom cable (OBC) experiment where receivers are located on the sea-floor, we have proposed combining the conventional marine surface seismic reflection data (streamer data) with OBC data. The streamer data add to the OBC data some of the wave paths needed for multiple attenuation. This combination has allowed us to develop a multiple attenuation method for OBC data which does not require any knowledge of the subsurface and which takes into account all free-surface multiples, including receiver ghosts. A non-linear synthetic data example consisting of pressure and particle velocity fields is used to illustrate the procedure.

show abstract

“…In practice, however, the source signature is unknown. Several strategies based on the suppression of multiples have been presented to estimate the operator A( f ) Carvalho & Weglein, 1994;van Borselen et al, 1996;Ikelle et al, 1997). In these studies, the estimation of the operator A( f ) is non-linear, which is an undesirable characteristic in the inversion process (Verschuur, 2006).…”

Section: Surface-related Multiple Elimination (Srme)mentioning

confidence: 99%

Determination of an Optimal Processing Flow for the Suppression of Free-Surface Multiples in Real 2d Marine Data

Gomes¹

2013

Rev. Bras. Geof.

View full text Add to dashboard Cite

ABSTRACT. The presence of multiple reflections is common in marine surveys due to the air-water interface. Multiples have significant energy and can mask deep reflectors, leading to the misinterpretation of seismic cross-sections. In this study, surface-related multiple elimination (SRME), predictive deconvolution in the τ − p domain and Radon and f − k filtering are used to eliminate surface multiples in real 2D marine data. These methods are applied in different combinations, and the results are analyzed with the aim of determining an optimal seismic processing flow for the removal of surface multiples.Keywords: surface multiples attenuation, SRME, Radon filtering, predictive deconvolution in the τ − p domain, f − k filtering. RESUMO.No levantamento marinhoé comum a presença de reflexões múltiplas devidoà interface ar-água. Essas reflexões múltiplas possuem energia considerável e podem mascarar reflexões primárias (refletores) levando a erros de interpretação da seção sísmica. Neste trabalhoé determinado um fluxoótimo de processamento sísmico para atenuação de múltiplas de superfície. Os métodos de eliminação de múltiplas de superfície (SRME), deconvolução preditiva no domínio τ − p e as filtragens Radon e f − k são aplicados a um dado marinho real 2D em diferentes combinações. Os resultados são analisados com objetivo de determinar um fluxo de processamento sísmicoótimo para atenuação de múltiplas de superfície.Palavras-chave: atenuação de múltiplas de superfície, SRME, filtragem Radon, deconvolução preditiva no domínio τ − p, filtragem f − k.

show abstract

Source signature estimation based on the removal of first‐order multiples

Cited by 46 publications

References 8 publications

Adaptive curvelet-domain primary-multiple separation

Adaptive curvelet-domain primary-multiple separation

Combining two seismic experiments to attenuate free‐surface multiples in OBC data*

Determination of an Optimal Processing Flow for the Suppression of Free-Surface Multiples in Real 2d Marine Data

Contact Info

Product

Resources

About