Abstract
High resolution imaging is of great value to an interpreter, for instance
to enable identification of small scale faults, and to locate formation
pinch-out positions. Standard approaches to obtain high-resolution
information, such as coherency analysis and structure-oriented filters,
derive attributes from stacked, migrated images. Since they are image-driven,
these techniques are sensitive to artifacts due to an inadequate
migration velocity; in fact the attribute derivation is not based
on the physics of wave propagation. Diffracted waves on the other
hand have been recognized as physically reliable carriers of high-
or even super-resolution structural information. However, high-resolution
information, encoded in diffractions, is generally lost during the
conventional processing sequence, indeed migration kernels in current
migration algorithms are biased against diffractions. We propose
here methods for a diffraction-based, data-oriented approach to image
resolution. We also demonstrate the different behaviour of diffractions
compared to specular reflections and how this can be leveraged to
assess characteristics of subsurface features. In this way a rough
surface such as a fault plane or unconformity may be distinguishable
on a diffraction image and not on a traditional reflection image.We
outline some characteristic properties of diffractions and diffraction
imaging, and present two novel approaches to diffraction imaging
in the depth domain. The first technique is based on reflection focusing
in the depth domain and subsequent filtering of reflections from
prestack data. The second technique modifies the migration kernel
and consists of a reverse application of stationary-phase migration
to suppress contributions from specular reflections to the diffraction
image. Both techniques are proposed as a complement to conventional
full-wave pre-stack depth migration, and both assume the existence
of an accurate migration velocity.
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