What’s Lurking in the Shadows? Seismic Shadow Zones

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I briefly illustrate how the propagation of seismic wavefields through the subsurface can lead to 'shadow zones' of imperfect seismic image quality. Using the foundation of image domain Least Squares Migration (LSM) introduced in previous articles, I also illustrate how shadow zones can be largely resolved.


The Origin of Shadow Zones in Seismic


Snapshots of a seismic wavefront as it propagates through a salt body. a) t = 6.7 seconds, b) t = 6.9 seconds, c) t = 7.2 seconds, and d) t = 7.5 seconds. The shot is located at x = 37000 ft. Shadow zones (refer to the next figure) correspond to ‘dim’ parts of the wavefront. From "Imaging by wave-equation inversion", PhD thesis, Alejandro Valenciano (2008).

The figure above shows four seismic wavefront snapshots as the wavefront propagates through a salt body. It should be obvious that the focusing and defocusing of such wavefronts as they propagate through complex geological features such as salt will result in some parts of the subsurface being illuminated with different reflection strength than other parts.

In the worst cases, ‘shadow zones’ are observed on the final migrated seismic images, as shown in the figure below.


Synthetic example of shadow zones in the migrated image below a salt body.

Furthermore, the next figure shows that the focusing and resolution of migrated images throughout the subsurface can vary strongly too.


The migrated impulse response for a uniform grid of point diffractors placed throughout a model containing a salt body (in the upper-right corner of the background image) show that not only do shadow zones occur below parts of the salt (annotated with red arrows), but the focusing and resolution of the migrated diffractors varies considerably throughout the subsurface, indicative of variable resolution in the overall migrated image.

Note that this figure shows a grid of Point Spread Functions (PSFs): the impulse response of a seismic imaging system to a point source or point object. Correspondingly, the degree of blurring of the point object is a measure of the quality of the imaging system.

Knowing the PSF is particularly useful inside shadow zones, as an appropriate inversion operation could reverse the spreading of the seismic energy and recover the amplitudes. As discussed below, after the migration is de-blurred by the inversion, the resulting image has more balanced amplitudes and better spatial resolution than the input image. Such an approach forms the basis of image domain Least Squares Migration (LSM).

I discussed the mathematical foundation of image domain LSM in a previous article I wrote titled "Least Squares Migration: 1 of 2 Articles" and will not repeat that here.

The next figure demonstrates the image uplift with synthetic seismic data. 


Synthetic examples of a salt model image produced using standard migration (left) and a least squares migration (right). On the right the reflectivity everywhere is far more balanced, events are clearly interpretable through the areas affected by shadow zones on the left, the amplitudes and focusing of the point diffractors everywhere are better, the vertical resolution everywhere is somewhat improved, and more obviously, and the resolution of dipping events (the ‘spatial resolution’) is noticeably better everywhere.

Summary

Image domain LSM is one of several possible LSM solutions to improve  the imaging of seismic data, but the point spread function (PSF) methodology provides a handy platform to illustrate the origin of some 'shadow zones' on seismic images.

Common to most traditional LSM implementation, the methodology enhances the reflectivity and spatial resolution of seismic images by comparison to one-pass pre-stack migration. However, the velocity model is not updated.

I do describe a solution to simultaneously update optimum models of subsurface reflectivity and velocity in "Least Squares Migration: 2 of 2 Articles".

Disclaimer

The content discussed here represents the opinion of Andrew Long only and may not be indicative of the opinions of Petroleum Geophysical AS or its affiliates ("PGS") or any other entity. Furthermore, material presented here is subject to copyright by Andrew Long, PGS, or other owners (with permission), and no content shall be used anywhere else without explicit permission. The content of this website is for general information purposes only and should not be used for making any business, technical or other decisions. 

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