Common-reflection-surface-based prestack diffraction separation and imaging

Abstract

Diffraction imaging can lead to high-resolution characterization of small-scale subsurface structures. A key step of diffraction imaging and tomography is diffraction separation and enhancement, especially in the full prestack data volume. We have considered point diffractors and developed a robust and fully data-driven workflow for prestack diffraction separation based on wavefront attributes, which are determined using the common-reflection-surface (CRS) method. In the first of two steps, we apply a zero-offset-based extrapolation operator for prestack diffraction separation, which combines the robustness and stability of the zero-offset CRS processing with enhanced resolution and improved illumination of the finite-offset CRS processing. In the second step, when the finite-offset diffracted events are separated, we apply a diffraction-based time migration velocity model building that provides high-quality diffraction velocity spectra. Applications of the new workflow to 2D/3D complex synthetic data confirm the superiority of prestack diffraction separation over the poststack method as well as the high potential of diffractions for improved time imaging.

When There Is No Offset: A Demonstration of Seismic Diffraction Imaging and Depth‐Velocity Model Building in the Southern Aegean Sea

“…For that reason, accessing the diffracted wavefield has been and still remains a major challenge to confront. In recent years, a range of methods has been introduced to arrive at approximate diffraction‐only images based, e.g., on modified versions of Kirchhoff's diffraction integral (e.g., Dafni & Symes, 2017; Moser & Howard, 2008; Yin & Nakata, 2017), specific versions of the Radon transformation and plane‐wave destruction filters (e.g., Fomel, 2002; Karimpouli et al, 2015), or multidimensional stacking (Bakhtiari Rad et al, 2018; Bauer et al, 2016; Dell & Gajewski, 2011). While the latter has the advantage of being directly applicable in the time domain without the need for specific data transformations and not requiring a detailed velocity model, the quality of the separation depends on the quality of the performed coherence measurements and the prestack data.…”

An introduction to seismic diffraction

“…In contrast to previously proposed strategies (e.g. Berkovitch et al, 2009;Dell and Gajewski, 2011;Bakhtiari Rad et al, 2018) which directly target the weak diffracted wavefield, a conventional reflection stack is suggested, followed by its subsequent adaptive subtraction from the full input wavefield,…”

Coherent diffraction imaging for enhanced fault and fracture network characterization

“…While some approaches introduced a diffraction bias in the migration scheme (Khaidukov et al, 2004;Moser and Howard, 2008;Klokov and Fomel, 2012), other strategies aim to extract the weak diffraction response in a separate step before imaging (e.g. Bansal and Imhof, 2005;Fomel et al, 2007).…”

“…Likewise applied before migration, there are some techniques that make direct use of wave-field coherence for diffraction separation (Berkovitch et al, 2009;Dell and Gajewski, 2011;Bauer et al, 2016;Bakhtiari Rad et al, 2018). While these methods specifically target the diffracted wave field for extraction, recent developments have shown that a more surgical, amplitude-preserving separation can be achieved by assessing the coherence of reflections instead (Schwarz and Gajewski, 2017a;Schwarz, 2019b).…”