Diffraction imaging in depth

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.