Imaging diffraction points using the local image matrices generated in prestack migration

Zhu, Xuwei; Wu, Ru‐Shan

doi:10.1190/1.3277252

Cited by 63 publications

(21 citation statements)

References 25 publications

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“…Several papers propose diffraction enhancement by modifying prestack Kirchhoff depth migration using appropriate weighting (Kozlov et al, 2004;Moser and Howard, 2008;Koren and Ravve, 2011). A similar approach in the local image matrices domain is presented by Zhu and Wu (2010).…”

Section: Introductionmentioning

confidence: 98%

Separation and imaging of seismic diffractions using migrated dip-angle gathers

2012

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Common-reflection angle migration can produce migrated gathers either in the scattering-angle domain or in the dip-angle domain. The latter reveals a clear distinction between reflection and diffraction events. We derived analytical expressions for events in the dip-angle domain and found that the shape difference can be used for reflection/ diffraction separation. We defined reflection and diffraction models in the Radon space. The Radon transform allowed us to isolate diffractions from reflections and noise. The separation procedure can be performed after either time migration or depth migration. Synthetic and real data examples confirmed the validity of this technique.

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Section: Introductionmentioning

confidence: 98%

Separation and imaging of seismic diffractions using migrated dip-angle gathers

2012

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“…During the last decade, there has been a steady rise in the interest to use diffracted waves for imaging and velocity estimation applications (Kozlov et al 2004;Moser and Howard 2008;Berkovitch et al 2009;Al-Dajani and Fomel 2010;Alonaizi et al 2013;Zhang and Zhang 2014;Sturzu et al 2014). In addition, the conventional Kirchoff migration algorithm has been modified to include diffractor points (Schmelzbach et al 2008;Malehmir, Bellefleur, and Müller 2010;Zhu and Wu 2010;Bellefleur, Malehmir, and Müller (2012). In addition, the conventional Kirchoff migration algorithm has been modified to include diffractor points (Schmelzbach et al 2008;Malehmir, Bellefleur, and Müller 2010;Zhu and Wu 2010;Bellefleur, Malehmir, and Müller (2012).…”

Section: Introductionmentioning

confidence: 99%

Anisotropy parameter inversion in vertical axis of symmetry media using diffractions

Waheed

Stovas

Alkhalifah

2016

Geophysical Prospecting

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Diffractions play a vital role in seismic processing as they can be utilized for high‐resolution imaging applications and analysis of subsurface medium properties like velocity. They are particularly valuable for anisotropic media as they inherently possess a wide range of dips necessary to resolve the angular dependence of velocity. However, until recently, the focus of diffraction imaging or inversion algorithms have been only on the isotropic approximation of the subsurface. Using diffracted waves, we develop a framework to invert for the effective η model. This effective model is obtained through scanning over possible effective η values and selecting the one that best fits the observed moveout curve for each diffractor location. The obtained effective η model is then converted to an interval η model using a Dix‐type inversion formula. The inversion methodology holds the potential to reconstruct the true η model with sufficiently high accuracy and resolution properties. However, it relies on an accurate estimation of diffractor locations, which in turn requires good knowledge of the background velocity model. We test the effectiveness and applicability of our method on the vertical transverse isotropic Marmousi model. The inversion results yield a reasonable match even for the complex Marmousi model.

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“…Examples include Fresnel aperture pre-stack depth migration (Hua and McMechan 2003;Tabti, Gellius, and Hellman 2004), data-driven automatic aperture optimization (Kabbej, Baina, and Duquet 2005), selecting migration apertures using dip-angle images (Klokov and Fomel 2013), or using local image matrices (Zhu and Wu 2010). Examples include Fresnel aperture pre-stack depth migration (Hua and McMechan 2003;Tabti, Gellius, and Hellman 2004), data-driven automatic aperture optimization (Kabbej, Baina, and Duquet 2005), selecting migration apertures using dip-angle images (Klokov and Fomel 2013), or using local image matrices (Zhu and Wu 2010).…”

Section: Introductionmentioning

confidence: 99%

Multipathing in three‐parameter common‐image gathers from reverse‐time migration

Zhang

Zhang²,

McMechan

et al. 2016

Geophysical Prospecting

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Reverse‐time migration gives high‐quality, complete images by using full‐wave extrapolations. It is thus not subject to important limitations of other migrations that are based on high‐frequency or one‐way approximations. The cross‐correlation imaging condition in two‐dimensional pre‐stack reverse‐time migration of common‐source data explicitly sums the product of the (forward‐propagating) source and (backward‐propagating) receiver wavefields over all image times. The primary contribution at any image point travels a minimum‐time path that has only one (specular) reflection, and it usually corresponds to a local maximum amplitude. All other contributions at the same image point are various types of multipaths, including prismatic multi‐arrivals, free‐surface and internal multiples, converted waves, and all crosstalk noise, which are imaged at later times, and potentially create migration artefacts. A solution that facilitates inclusion of correctly imaged, non‐primary arrivals and removal of the related artefacts, is to save the depth versus incident angle slice at each image time (rather than automatically summing them). This results in a three‐parameter (incident angle, depth, and image time) common‐image volume that integrates, into a single unified representation, attributes that were previously computed by separate processes. The volume can be post‐processed by selecting any desired combination of primary and/or multipath data before stacking over image time. Separate images (with or without artifacts) and various projections can then be produced without having to remigrate the data, providing an efficient tool for optimization of migration images. A numerical example for a simple model shows how primary and prismatic multipath contributions merge into a single incident angle versus image time trajectory. A second example, using synthetic data from the Sigsbee2 model, shows that the contributions to subsalt images of primary and multipath (in this case, turning wave) reflections are different. The primary reflections contain most of the information in regions away from the salt, but both primary and multipath data contribute in the subsalt region.

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Imaging diffraction points using the local image matrices generated in prestack migration

Cited by 63 publications

References 25 publications

Separation and imaging of seismic diffractions using migrated dip-angle gathers

Separation and imaging of seismic diffractions using migrated dip-angle gathers

Anisotropy parameter inversion in vertical axis of symmetry media using diffractions

Multipathing in three‐parameter common‐image gathers from reverse‐time migration

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