A multi‐angle toolbox for restored amplitude images and AVA‐Gathers

Audebert, F.; Froidevaux, Pascal; Huard, Irène; Nicoletis, L.; Svay-Lucas, J.

doi:10.1190/1.1815556

Cited by 15 publications

(4 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To meet this requirement, some Voronoi binning can be applied beforehand. At this point appeared another family of true amplitude approaches, that perform an explicit regularization of illumination at the depth point: the microlocal inversion in the angle domain of Brandsberg-dahl et al (1999), the regularization of dip in the offset domain of Albertin et al (1999), and two different implementations of the regularization of illumination in the dip angle and scattering angle domains, Rousseau et al (2000) and Audebert et al (2000). The present paper is a follow-up on this latter paper.…”

Section: Introductionmentioning

confidence: 93%

Insights into migration in the angle domain

Audebert

Froidevaux

Rakotoarisoa

et al. 2002

SEG Technical Program Expanded Abstracts 2002

Self Cite

View full text Add to dashboard Cite

We examine some aspects of the Kirchhoff migration in the angle domains. The angle domains we refer to are the scattering angle domain (both opening and azimuth of scattering), which replaces the surface related offset and azimuth of acquisition, and the illumination dip angle domain (having two components in 3D). We examine the insight given to the Kirchhoff summation and to the stationary phase approximation, by virtue of the decomposition of the migration in the illumination dip angle domain. Additionally we point out some differences between angle domain and offset domain migration.

show abstract

Section: Introductionmentioning

confidence: 93%

Insights into migration in the angle domain

Audebert

Froidevaux

Rakotoarisoa

et al. 2002

SEG Technical Program Expanded Abstracts 2002

Self Cite

View full text Add to dashboard Cite

show abstract

“…These authors illustrate this fact in two dimensions using multiarrival Kirchhoff migration on the Marmousi synthetic data set (Lailly et al, 1991). Subsequent research has extended this work to anisotropic media (Alerini and Ursin, 2009;Alkhalifah and Fomel, 2009) or three dimensions using CIGs in the reflection angle/ azimuth angle, and to 3D analysis in the multiple angle domain (reflection angle, dip angle, azimuthal angle, and so on) (Audebert et al, 2000;Koren et al, 2008).…”

Section: Introductionmentioning

confidence: 97%

3D angle gathers from reverse time migration

Xu¹,

Zhang²,

Tang³

2011

GEOPHYSICS

226

View full text Add to dashboard Cite

Common-image gathers are an important output of prestack depth migration. They provide information needed for velocity model building and amplitude and phase information for subsurface attribute interpretation. Conventionally, common-image gathers are computed using Kirchhoff migration on commonoffset/azimuth data volumes. When geologic structures are complex and strong contrasts exist in the velocity model, the complicated wave behaviors will create migration artifacts in the image gathers. As long as the gather output traces are indexed by any surface attribute, such as source location, receiver location, or surface plane-wave direction, they suffer from the migration artifacts caused by multiple raypaths. These problems have been addressed in a significant amount of work, resulting in common-image gathers computed in the reflection angle domain, whose traces are indexed by the subsurface reflection angle and/or the subsurface azimuth angle.Most of these efforts have concentrated on Kirchhoff and oneway wave-equation migration methods. For reverse time migration, subsurface angle gathers can be produced using the same approach as that used for one-way wave-equation migration. However, these approaches need to be revisited when producing high-quality subsurface angle gathers in three dimensions (reflection angle/azimuth angle), especially for wide-azimuth data. We have developed a method for obtaining 3D subsurface reflection angle/azimuth angle common-image gathers specifically for the amplitude-preserved reverse time migration. The method builds image gathers with a highdimensional convolution of wavefields in the wavenumber domain. We have found a windowed antileakage Fourier transform method that leads to an efficient and practical implementation. This approach has generated high-resolution angle-domain gathers on synthetic 2.5D data and 3D wideazimuth real data.

show abstract

“…While some ray-based and wave-equation-based migration algorithms provide some separation of arrivals, these usually select, at each image point, a single (or a few) specific arrival, such as those with the earliest times, the strongest amplitudes (Audebert et al 2000;Operto, Xu, and Lambaré 2000;McMechan 2013, 2015), ranges of incident, or reflected angles (e.g., Zhang and McMechan 2010;Xu, Zhang, and Tang 2011) prior to migration; therefore, it cannot be changed without remigrating. Wave-based algorithms that use the cross-correlation imaging condition use all arrivals that are present (e.g., Whitmore and Lines 1986;Zhang, Sun, and Gray 2007).…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Zhang²,

McMechan

et al. 2016

Geophysical Prospecting

View full text Add to dashboard Cite

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.

show abstract

A multi‐angle toolbox for restored amplitude images and AVA‐Gathers

Cited by 15 publications

References 1 publication

Insights into migration in the angle domain

Insights into migration in the angle domain

3D angle gathers from reverse time migration

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

Contact Info

Product

Resources

About