Data‐driven internal multiple attenuation — Applications and issues on land data

Kelamis, Panos G.; Erickson, Kevin; Clark, Robert L.; Burnstad, Roy; Verschuur, Eric

doi:10.1190/1.1817099

Cited by 18 publications

(9 citation statements)

References 7 publications

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“…The mask filter has been used in the f-k domain, Radon transform domain, or the t-x domain for multiple attenuation to reduce the leakage of primary energy ͑Zhou and Greenhalgh, 1994Greenhalgh, , 1996Landa et al, 1999;Kelamis et al, 2002;Wang, 2003a͒. Guitton ͑2005͒ also used a masking operator in the pattern-based multiple attenuation method, which defined the operator as a diagonal matrix filled with zeros and ones, to preserve the signal when there are no multiples.…”

Section: Multiple Subtraction With a Masking Filtermentioning

confidence: 99%

“…Moreover, this iteration is performed in the subtraction step, and it is numerically cheaper than a similar iteration implementation adopted in the more expensive multiple modeling step to improve the dynamic properties of multiple models ͑Berkhout and Wang, 2004 Second, masking the data prior to multiple suppression also is an essential factor in the process. The basic idea ͑Zhou and Greenhalgh, 1994Greenhalgh, , 1996Landa et al, 1999;Kelamis et al, 2002;Wang, 2003a͒ is to use predicted multiples as references to design a masking filter so as to separate most of the primary energy. We apply it during adaptive subtraction in the t-x domain, before adaptively subtracting modeled multiples from only the remaining part.…”

Section: Introductionmentioning

confidence: 99%

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Improving adaptive subtraction in seismic multiple attenuation

Huo

Wang

2009

GEOPHYSICS

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In seismic multiple attenuation, once the multiple models have been built, the effectiveness of the processing depends on the subtraction step. Usually the primary energy is partially attenuated during the adaptive subtraction if an L 2 -norm matching filter is used to solve a least-squares problem. The expanded multichannel matching ͑EMCM͒ filter generally is effective, but conservative parameters adopted to preserve the primary could lead to some remaining multiples. We have managed to improve the multiple attenuation result through an iterative application of the EMCM filter to accumulate the effect of subtraction. A Butterworth-type masking filter based on the multiple model can be used to preserve most of the primary energy prior to subtraction, and then subtraction can be performed on the remaining part to better suppress the multiples without affecting the primaries. Meanwhile, subtraction can be performed according to the orders of the multiples, as a single subtraction window usually covers different-order multiples with different amplitudes. Theoretical analyses, and synthetic and real seismic data set demonstrations, proved that a combination of these three strategies is effective in improving the adaptive subtraction during seismic multiple attenuation.

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Section: Multiple Subtraction With a Masking Filtermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving adaptive subtraction in seismic multiple attenuation

Huo

Wang

2009

GEOPHYSICS

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“…The articles of Verschuur et al (1992), Berkhout (1997), Weglein et al (1997), Dragoset and Jericevic (1998), Jakubowicz (1998), Berkhout (1999), Verschuur and Berkhout (2001), Kelamis et al (2002), and Erez and Ikelle (2005), represent a part of the significant efforts made by the geophysical community in the recent years on the way to resolve the problems caused by those aspects in seismic processing. In particular, Jakubowicz (1998), showed that the equation describing the relation between internal multiples, the data and the primary events is:…”

Section: D Internal Multiple Modelingmentioning

confidence: 99%

Wave equation based internal multiple modeling in 3D

Pica

2008

SEG Technical Program Expanded Abstracts 2008

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Model-based surface related multiple modeling (3D SRMM) can be achieved by the use of pre-stack demigration algorithms, thus avoiding the constrains on the shot positions distribution required by the data-based methods. In the following, we show a new method for modeling internal multiples in 3D by using a model-based technique. This method follows a parallel flow with respect to those employed by the data-based multiple modeling techniques, and allows for the construction of internal multiple events produced between upper layers reflecting the energy downward, and lower layers reflecting the energy upward. The method has been applied to Wide Azimuth Towed Streamer data from the Gulf of Mexico.

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“…This idea is fundamental to surface-related ͑SRME͒ and internal multiple estimation techniques of Verschuur, 1997, 2005;Berkhout, 1997, 2005͒; other authors have also built upon these ideas ͑Fokkema et al, 1994; Kelamis et al, 2002;van Borselen, 2002͒. The technique discussed here has its roots in these ideas but differs from other methods because we propose estimating, directly in the image, artifacts caused by internal multiples ͑IM͒.…”

Section: Introductionmentioning

confidence: 99%

“…At present, significantly more is known about attenuation of surface-related multiples ͑Anstey and Newman, 1966;Kennett, 1974;Aminzadeh and Mendel, 1980;Fokkema and van den Berg, 1993;Berkhout and Verschuur, 1997;Verschuur and Berkhout, 1997;Weglein et al, 1997 than is known about attenuation of internal multiples ͑Fokke-ma et al., 1994;Weglein et al, 1997;Jakubowicz, 1998;Kelamis et al, 2002;ten Kroode, 2002;van Borselen, 2002;Weglein et al, 2003;Berkhout and Verschuur, 2005;Verschuur and Berkhout, 2005͒. With the exception of techniques such as the angle-domain filtering proposed by Sava and Guitton ͑2005͒ and the image-domain surface-related multiple prediction technique of Artman and Matson ͑2006͒, the current state of the art in multiple attenuation involves estimating multiples in the data.…”

Section: Introductionmentioning

confidence: 99%

Identification of image artifacts from internal multiples

2007

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First-order internal multiples are a source of coherent noise in seismic images because they do not satisfy the single-scattering assumption fundamental to most seismic processing. There are a number of techniques to estimate internal multiples in data; in many cases, these algorithms leave some residual multiple energy in the data. This energy produces artifacts in the image, and the location of these artifacts is unknown because the multiples were estimated in the data before the image was formed. To avoid this problem, we propose a method by which the artifacts caused by internal multiples are estimated directly in the image. We use ideas from the generalized Bremmer series and the LippmannSchwinger scattering series to create a forward-scattering series to model multiples and an inverse-scattering series to describe the impact these multiples have on the common-image gather and the image. We present an algorithm that implements the third term of this series, responsible for the formation of first-order internal multiples. The algorithm works as part of a wave-equation migration; the multiple estimation is made at each depth using a technique related to one used to estimate surface-related multiples. This method requires knowledge of the velocity model to the depth of the shallowest reflector involved in the generation of the multiple of interest. This information allows us to estimate internal multiples without assumptions inherent to other methods. In particular, we account for the formation of caustics. Results of the techniques on synthetic data illustrate the kinematic accuracy of predicted multiples, and results on field data illustrate the potential of estimating artifacts caused by internal multiples in the image rather than in the data.

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Data‐driven internal multiple attenuation — Applications and issues on land data

Cited by 18 publications

References 7 publications

Improving adaptive subtraction in seismic multiple attenuation

Improving adaptive subtraction in seismic multiple attenuation

Wave equation based internal multiple modeling in 3D

Identification of image artifacts from internal multiples

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