1‐D analytical analysis of higher order internal multiples predicted via the inverse scattering series based algorithm

2010 ◽  
Author(s):  
Haiyan Zhang ◽  
Simon Shaw
Keyword(s):  
Inverse Scattering ◽  
Higher Order ◽  
Analytical Analysis ◽  
Inverse Scattering Series ◽  
Internal Multiples

scholarly journals Relating source-receiver interferometry to an inverse-scattering series to derive a new method to estimate internal multiples

Geophysics ◽  
2016 ◽  
Vol 81 (3) ◽  
pp. Q27-Q40 ◽  
Author(s):  
Katrin Löer ◽  
Andrew Curtis ◽  
Giovanni Angelo Meles
Keyword(s):  
Inverse Scattering ◽  
Computational Cost ◽  
Synthetic Data ◽  
Data Set ◽  
Inverse Scattering Series ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
New Formula ◽  
3D Applications ◽  
Insight Into

We have evaluated an explicit relationship between the representations of internal multiples by source-receiver interferometry and an inverse-scattering series. This provides a new insight into the interaction of different terms in each of these internal multiple prediction equations and explains why amplitudes of estimated multiples are typically incorrect. A downside of the existing representations is that their computational cost is extremely high, which can be a precluding factor especially in 3D applications. Using our insight from source-receiver interferometry, we have developed an alternative, computationally more efficient way to predict internal multiples. The new formula is based on crosscorrelation and convolution: two operations that are computationally cheap and routinely used in interferometric methods. We have compared the results of the standard and the alternative formulas qualitatively in terms of the constructed wavefields and quantitatively in terms of the computational cost using examples from a synthetic data set.

Internal multiple prediction using inverse-scattering series with sparsity promotion — Part 1: Background, analysis, and synthetic modeling

Geophysics ◽  
2021 ◽  
pp. 1-94
Author(s):  
Ole Edvard Aaker ◽  
Adriana Citlali Ramírez ◽  
Emin Sadikhov
Keyword(s):  
Plane Wave ◽  
Inverse Scattering ◽  
Seismic Data ◽  
Data Completeness ◽  
Inverse Scattering Series ◽  
Recent Developments ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
Synthetic Modeling ◽  
The Way

The presence of internal multiples in seismic data can lead to artefacts in subsurface images ob-tained by conventional migration algorithms. This problem can be ameliorated by removing themultiples prior to migration, if they can be reliably estimated. Recent developments have renewedinterest in the plane wave domain formulations of the inverse scattering series (ISS) internal multipleprediction algorithms. We build on this by considering sparsity promoting plane wave transformsto minimize artefacts and in general improve the prediction output. Furthermore, we argue forthe usage of demigration procedures to enable multidimensional internal multiple prediction withmigrated images, which also facilitate compliance with the strict data completeness requirementsof the ISS algorithm. We believe that a combination of these two techniques, sparsity promotingtransforms and demigration, pave the way for a wider application to new and legacy datasets.

Internal multiple prediction using inverse scattering series withsparsity promotionPart II: Application strategy and field data examples

Geophysics ◽  
2021 ◽  
pp. 1-52
Author(s):  
Ole Edvard Aaker ◽  
Adriana Citlali Ramírez ◽  
Emin Sadikhov
Keyword(s):  
Inverse Scattering ◽  
Field Data ◽  
Norwegian Sea ◽  
Prediction Quality ◽  
Inverse Scattering Series ◽  
Exploration And Production ◽  
Internal Multiples ◽  
Multiple Prediction ◽  
Seismic Images

Incorrect imaging of internal multiples can lead to substantial imaging artefacts. It is estimatedthat the majority of seismic images available to exploration and production companies have had nodirect attempt at internal multiple removal. In Part I of this article we considered the role of spar-sity promoting transforms for improving practical prediction quality for algorithms derived fromthe inverse scattering series (ISS). Furthermore, we proposed a demigration-migration approach toperform multidimensional internal multiple prediction with migrated data and provided a syntheticproof of concept. In this paper (Part II) we consider application of the demigration-migration approach to field data from the Norwegian Sea, and provide a comparison to a post-stack method (froma previous related work). Beyond application to a wider range of data with the proposed approach,we consider algorithmic and implementational optimizations of the ISS prediction algorithms tofurther improve the applicability of the multidimensional formulations.

scholarly journals Comparison of monotonicity challenges encountered by the inverse scattering series and the Marchenko demultiple method for elastic waves

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. Q11-Q26
Author(s):  
C. Reinicke ◽  
M. Dukalski ◽  
K. Wapenaar
Keyword(s):  
Inverse Scattering ◽  
Acoustic Waves ◽  
Prior Information ◽  
Monotonicity Condition ◽  
Scattering Media ◽  
Coupled Modes ◽  
Inverse Scattering Series ◽  
Temporal Event Ordering ◽  
Internal Multiples ◽  
The Time Domain

The reflection response of strongly scattering media often contains complicated interferences between primaries and (internal) multiples, which can lead to imaging artifacts unless handled correctly. Internal multiples can be kinematically predicted, for example by the Jakubowicz method or by the inverse scattering series (ISS), as long as monotonicity, that is, “correct” temporal event ordering, is obeyed. Alternatively, the (conventional) Marchenko method removes all overburden-related wavefield interactions by formulating an inverse problem that can be solved if the Green’s and the so-called focusing functions are separable in the time domain, except for an overlap that must be predicted. For acoustic waves, the assumptions of the aforementioned methods are often satisfied within the recording regimes used for seismic imaging. However, elastic media support wave propagation via coupled modes that travel with distinct velocities. Compared to the acoustic case, not only does the multiple issue become significantly more severe, but also violation of monotonicity becomes much more likely. By quantifying the assumptions of the conventional Marchenko method and the ISS, unexpected similarities as well as differences between the requirements of the two methods come to light. Our analysis demonstrates that the conventional Marchenko method relies on a weaker form of monotonicity. However, this advantage must be compensated by providing more prior information, which in the elastic case is an outstanding challenge. Rewriting, or remixing, the conventional Marchenko scheme removes the need for prior information but leads to a stricter monotonicity condition, which is now almost as strict as for the ISS. Finally, we introduce two strategies on how the remixed Marchenko solutions can be used for imperfect, but achievable, demultiple purposes.

Elimination of land internal multiples based on the inverse scattering series

2011 ◽  
Vol 30 (8) ◽  
pp. 884-889 ◽  
Author(s):  
Yi Luo ◽  
Panos G. Kelamis ◽  
Qiang Fu ◽  
ShouDong Huo ◽  
Ghada Sindi ◽  
...  
Keyword(s):  
Inverse Scattering ◽  
Inverse Scattering Series ◽  
Internal Multiples

The inverse scattering series approach towards the elimination of land internal multiples

2010 ◽  
Author(s):  
Qiang Fu ◽  
Yi Luo ◽  
Panos G. Kelamis ◽  
ShouDong Huo ◽  
Ghada Sindi ◽  
...  
Keyword(s):  
Inverse Scattering ◽  
Inverse Scattering Series ◽  
Internal Multiples
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