Fast-Track, Data-Driven Interbed Multiple Removal - a North Sea Data Example

Borselen, R.G. van

doi:10.3997/2214-4609-pdb.5.f040

Cited by 14 publications

(8 citation statements)

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“…It is interesting to remark that can be used to predict interbed multiples by using only surface data and simple muting operations, followed by adaptive subtraction, combining the work of Jakubowicz (1998) and Verschuur and Berkhout (1997). This was demonstrated by Moore (2001) and van Borselen (2002). We will combine the best elements from these papers with the EPSI method from Van Groenestijn and Verschuur (2009a): removing surface‐ and interbed multiples using only surface data, without the need of the typical adaptive subtraction step.…”

Section: The Primary‐multiple Model Surface‐related Multiple Eliminamentioning

confidence: 99%

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Estimating primaries by sparse inversion, a generalized approach

Ypma¹,

Verschuur²

2012

Geophysical Prospecting

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A B S T R A C TFor an accurate interpretation of seismic data, multiple-free data are of great value. Removing surface multiples and interbed multiples proves to be challenging in many cases. The nowadays widely used method of Surface-Related Multiple Elimination (SRME) has lately been redefined as a full-waveform inversion process, resulting in the method of Estimation of Primaries by Sparse Inversion (EPSI). The new method is shown to be more accurate than the former method in several situations, because it estimates primaries such that they, together with their multiples, explain the input data. Its main advantage is that the minimum energy assumption in traditional multiple subtraction is avoided. The SRME methodology has been extended to the case of internal multiples by several authors, however, the involved subtraction of predicted multiples is probably even more challenging than for the surface-multiple case. Therefore, in this paper the EPSI method is generalized to remove both surface and interbed multiples. As in previous implementations of internal multiple removal based on data-driven convolution, the newly proposed scheme requires some knowledge about the subsurface: the data should be divided into (macro) layers and appropriate time windows must be selected. The method is tested on two 2D synthetic datasets to prove its viability. Furthermore, application to a 2D field dataset showed improved accuracy compared to conventional prediction and subtraction.

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Section: The Primary‐multiple Model Surface‐related Multiple Eliminamentioning

confidence: 99%

“…Note, that if in this paper we refer to the IME method, we mean the data‐driven convolution process and not the ISS method. The IME methods have been proven effective on field data, as shown by e.g., Moore (2001), van Borselen (2002), El‐Emam, Moore and Shabrawi (2005) and Hembd et al (2010).…”

Section: Introductionmentioning

confidence: 99%

Estimating primaries by sparse inversion, a generalized approach

Ypma¹,

Verschuur²

2012

Geophysical Prospecting

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“…In standard migration images, strong artifacts can occur due to internal multiple reflections in marine (Hadidi and Verschuur, 1997;Van Borselen, 2002) and land seismic data (Kelamis et al, 2006). Several schemes have been proposed to predict and subtract internal multiple reflections from measured data before the imaging procedure, such as internal multiple elimination (Berkhout and Ver-schuur, 2005) and inverse scattering series (ISS) (Weglein et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

Transmission compensated primary reflection retrieval in the data domain and consequences for imaging

et al. 2019

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We have developed a scheme that retrieves primary reflections in the two-way traveltime domain by filtering the data. The data have their own filter that removes internal multiple reflections, whereas the amplitudes of the retrieved primary reflections are compensated for two-way transmission losses. Application of the filter does not require any model information. It consists of convolutions and correlations of the data with itself. A truncation in the time domain is applied after each convolution or correlation. The retrieved data set can be used as the input to construct a better velocity model than the one that would be obtained by working directly with the original data and to construct an enhanced subsurface image. Two 2D numerical examples indicate the effectiveness of the method. We have studied bandwidth limitations by analyzing the effects of a thin layer. The presence of refracted and scattered waves is a known limitation of the method, and we studied it as well. Our analysis indicates that a thin layer is treated as a more complicated reflector, and internal multiple reflections related to the thin layer are properly removed. We found that the presence of refracted and scattered waves generates artifacts in the retrieved data.

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“…Jakubowicz (1998) proposed the surface-based IME method, in which the need for CFP gathers in the boundary-related method is avoided, and internal multiples can be estimated directly from the data measured on the surface. In van Borselen (2002), an extension of this procedure is illustrated to remove internal multiples that have crossed a pseudo-boundary that is chosen to lie between two internal reflectors. Thus, the data-driven internal multiple elimination based on surface data can be applied either in boundary-related version or layerrelated version.…”

Section: Introductionmentioning

confidence: 99%

Surface-based Internal Multiple Elimination in the CMP Domain — Theory and Application Strategies on Land Seismic Data

2016

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The data-driven internal multiple elimination (IME) method based on feedback model, which includes CFP-based, surface-based and inversion-based methods, are successfully applied to marine datasets. However, these methods are computationally expensive and not always straightforward on land datasets. In this paper, we first proved that the surface-based IME method, which is the most computationally efficient method among the three methods, can be derived from the CFP theory. Then we extend it to CMP domain under the assumption of locally lateral invariance of the earth, which makes it more computationally efficient. In addition, we proposed applying a time-variant taper based on the first Fresnel zone to predict the multiples more percisely. Besides, the improved S/N ratio and dense offset distribution can be obtained by using the CMP supergather, which makes the CMP-oriented method more suitable for land data. Some practical processing strategies are proposed via case study. The effectiveness of the proposed method is demonstrated with the application to synthetic and field data.

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Fast-Track, Data-Driven Interbed Multiple Removal - a North Sea Data Example

Cited by 14 publications

References 0 publications

Estimating primaries by sparse inversion, a generalized approach

Estimating primaries by sparse inversion, a generalized approach

Transmission compensated primary reflection retrieval in the data domain and consequences for imaging

Surface-based Internal Multiple Elimination in the CMP Domain — Theory and Application Strategies on Land Seismic Data

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