Data‐driven interbed multiple removal: Strategies and examples

Borselen, Roald van

doi:10.1190/1.1817119

Cited by 7 publications

(7 citation statements)

References 5 publications

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“…Moreover, the reflection response can contain head and surface waves (purple). data) to the scheme by van Borselen (2002) and Ikelle (2006), and thus, we review the two latter ones first.…”

Section: Data-driven Multiple Eliminationmentioning

confidence: 99%

“…Next, e.g. using van Borselen (2002), first order multiples with two bounces below and one above the aforementioned pseudo-boundary are kinematically predicted using temporal data correlation and convolution according to,…”

Section: Data-driven Multiple Eliminationmentioning

confidence: 99%

“…In acoustic media, these requirements can be realistically met. The multi-component data can be reduced to a single (compressional) mode and the temporal mute is derived from a single pseudo-boundary (similarly to the mute used by van Borselen, 2002;Berkhout and Verschuur, 2005;Ikelle, 2006). The assumption (iii), monotonicity, requires "correct" temporal ordering of events (Nita and Weglein, 2009;ten Kroode, 2002).…”

Section: Introductionmentioning

confidence: 99%

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Internal multiple elimination: Can we trust an acoustic approximation?

Reinicke

Dukalski²,

Wapenaar

2021

GEOPHYSICS

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Correct handling of strong elastic, internal, multiples remains a challenge for seismic imaging. Methods aimed at eliminating them are currently limited by monotonicity violations, a lack of a-priori knowledge about mode conversions, or unavailability of multi-component sources and receivers for not only particle velocities but also the traction vector. Most of these challenges vanish in acoustic media such that Marchenko-equation-based methods are able in theory to remove multiples exactly (within a certain wavenumber-frequency band). In practice, however, when applied to (elastic) field data, mode conversions are unaccounted for. Aiming to support a recently published marine field data study, we build a representative synthetic model. For this setting, we demonstrate that mode conversions can have a substantial impact on the recovered multiple-free reflection response. Nevertheless, the images are significantly improved by acoustic multiple elimination. Moreover, after migration the imprint of elastic effects is considerably weaker and unlikely to alter the seismic interpretation.

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“…Moreover, the reflection response can contain head and surface waves (purple). data) to the scheme by van Borselen (2002) and Ikelle (2006), and thus, we review the two latter ones first.…”

Section: Data-driven Multiple Eliminationmentioning

confidence: 99%

Section: Data-driven Multiple Eliminationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Internal multiple elimination: Can we trust an acoustic approximation?

Reinicke

Dukalski²,

Wapenaar

2021

GEOPHYSICS

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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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A method for inverse scattering based on the generalized Bremmer coupling series

Malcolm¹,

Hoop²

2005

Inverse Problems

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Imaging with seismic data is typically done under the assumption of single scattering. Here we formulate a theory that includes multiply scattered waves in the imaging process. We develop both a forward and an inverse scattering series derived from the Lippmann-Schwinger equation and the Bremmer coupling series. We estimate leading-order internal multiples explicitly using the third term of the forward series. From the inverse series, two images are constructed, one formed with all the data, the other with the estimated leading-order internal multiples; the final image is formed from the difference of these two images. We combine the modelling of the leading-order internal multiples with the construction of the second image resulting in one two-part imaging procedure.

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Data‐driven interbed multiple removal: Strategies and examples

Cited by 7 publications

References 5 publications

Internal multiple elimination: Can we trust an acoustic approximation?

Internal multiple elimination: Can we trust an acoustic approximation?

Identification of image artifacts from internal multiples

A method for inverse scattering based on the generalized Bremmer coupling series

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