Diffraction imaging by focusing‐defocusing: An outlook on seismic superresolution

Abstract

Diffractions always need more advertising. It is true that conventional seismic processing and migration are usually successful in using specular reflections to estimate subsurface velocities and reconstruct the geometry and strength of continuous and pronounced reflectors. However, correct identification of geological discontinuities, such as faults, pinch‐outs, and small‐size scattering objects, is one of the main objectives of seismic interpretation. The seismic response from these structural elements is encoded in diffractions, and diffractions are essentially lost during the conventional processing/migration sequence. Hence, we advocate a diffraction‐based, data‐oriented approach to enhance image resolution—as opposed to the traditional image‐oriented techniques, which operate on the image after processing and migration. Even more: it can be shown that, at least in principle, processing of diffractions can lead to superresolution and the recovery of details smaller than the seismic wavelength. The so‐called reflection stack is capable of effectively separating diffracted and reflected energy on a prestack shot gather by focusing the reflection to a point while the diffraction remains unfocused over a large area. Muting the reflection focus and defocusing the residual wavefield result in a shot gather that contains mostly diffractions. Diffraction imaging applies the classical (isotropic) diffraction stack to these diffraction shot gathers. This focusing‐muting‐defocusing approach can successfully image faults, small‐size scattering objects, and diffracting edges. It can be implemented both in model‐independent and model‐dependent contexts. The resulting diffraction images can greatly assist the interpreter when used as a standard supplement to full‐wave images.

Towards a Mathematical Theory of Super‐resolution

“…Here, there is an inflexible limit to the effective resolution of a whole system due to photon shot noise, which degrades image quality when pixels are made smaller. Some other fields where it is desirable to extrapolate fine-scale details from low-resolution data-or resolve subpixel details-include spectroscopy [24], radar [30], nonoptical medical imaging [26], and geophysics [27]. For a survey of super-resolution techniques in imaging, see [31] and the references therein.…”

Coal seismic diffraction fault imaging: Results from numerical modelling

“…transform) for separating diffractions from reflections for velocity estimation on post-stack sections. Khaidukov et al (2004) and Berkovitch et al (2009) extracted the diffractions by muting the focused imaginary source points from reflections on a prestack shot gather. Taner et al (2006) used plane-wave destruction filter to suppress reflections and retain diffractions.…”

“…Prior to using seismic migration, seismic interpreters sought diffraction patterns as an indication of faulting structures, especially for small faults where the discontinuities in the seismic reflections are less evident. These diffractions are often attenuated by conventional seismic data processing (Khaidukov et al, 2004;Bansal and Imhof, 2005;Moser and Howard, 2008). However, the significance of these diffractions has been long recognised in fault and other discontinuity imaging by many researchers such as Krey (1952), Hagedoorn (1954), Trorey (1970), Harlan et al (1984), Landa et al (1987), Kanasewich and Phadke (1988), Neidell (1997), Khaidukov et al (2004), Shtivelman and Keydar (2004) and Landa (2010).…”

“…Many approaches and applications have been developed for diffraction imaging. The key applications of diffractions are for detections of faults and fractures (Khaidukov et al, 2004;Cheng and Hilterman, 2007;Al-Dajani and Fomel, 2010;Zhu and Wu, 2010) and migration velocity analysis (Harlan et al, 1984;Soellner, and Yang, 2002;Sava et al, 2005;Fomel et al, 2007;Landa and Fomel, 2008;Reshef and Landa, 2009 Currently, all the reported examples are petroleum exploration oriented, where targets are relatively deep and the seismic frequencies are relatively low around 10 -60 Hz. In this paper, we apply the diffraction imaging techniques to enhance the detectability of small faults for coal seismic environments and demonstrate the feasibility of a new fault imaging method with numerical examples.…”

Fundamental controls on fluid flow in carbonates: current workflows to emerging technologies

“…FAZ and long-offset data can be used for lithology prediction but this requires specialized processing that has yet to mature (Hall et al 2008). The use of diffractions to image fractures and karst in carbonate reservoirs has also advanced (Khaidukov et al 2004;Fomel et al 2007;Koren & Ravve 2011). However, challenges for diffraction imaging require access to the diffracted wavefield, separation of the diffraction from the reflection and imaging of the diffracted wavefield (Reshef & Landa 2009;Klokov & Fomel 2012).…”