Directional‐oriented wavefield imaging: a new wave‐based subsurface illumination imaging condition for reverse time migration

Abstract

The key objective of an imaging algorithm is to produce accurate and high‐resolution images of the subsurface geology. However, significant wavefield distortions occur due to wave propagation through complex structures and irregular acquisition geometries causing uneven wavefield illumination at the target. Therefore, conventional imaging conditions are unable to correctly compensate for variable illumination effects. We propose a generalised wave‐based imaging condition, which incorporates a weighting function based on energy illumination at each subsurface reflection and azimuth angles. Our proposed imaging kernel, named as the directional‐oriented wavefield imaging, compensates for illumination effects produced by possible surface obstructions during acquisition, sparse geometries employed in the field, and complex velocity models. An integral part of the directional‐oriented wavefield imaging condition is a methodology for applying down‐going/up‐going wavefield decomposition to both source and receiver extrapolated wavefields. This type of wavefield decomposition eliminates low‐frequency artefacts and scattering noise caused by the two‐way wave equation and can facilitate the robust estimation for energy fluxes of wavefields required for the seismic illumination analysis. Then, based on the estimation of the respective wavefield propagation vectors and associated directions, we evaluate the illumination energy for each subsurface location as a function of image depth point and subsurface azimuth and reflection angles. Thus, the final directional‐oriented wavefield imaging kernel is a cross‐correlation of the decomposed source and receiver wavefields weighted by the illuminated energy estimated at each depth location. The application of the directional‐oriented wavefield imaging condition can be employed during the generation of both depth‐stacked images and azimuth–reflection angle‐domain common image gathers. Numerical examples using synthetic and real data demonstrate that the new imaging condition can properly image complex wave paths and produce high‐fidelity depth sections.

Least squares reverse time migration imaging with illumination preconditioned based on improved PRP conjugate gradients

“…As for the development of conjugate gradient algorithm and illumination preprocessing, Liu et al 15 performed time-domain full waveform inversion for eight versions of the CG method, and numerical experiments showed that the PRP conjugate gradient (PRPCG) method is more efficient. Kim et al 16 proposed direction-oriented wavefield imaging, which compensates for possible illumination effects during acquisition and can produce high-fidelity depth profiles and correct imaging of complex wavepaths. Yu et al 17 developed a 3D nonlinear conjugate gradient traveltime inversion method using the PRP conjugate gradient method for solving constrained damping least squares problems, and model tests showed that the method can substantially improve the inversion resolution.…”

An illumination‐compensated Gaussian beam migration for enhancing subsalt imaging

“…Salt basins, like the Gulf of Mexico and Angola, are one of most prospective places for oil and gas exploration (Leveille et al ., 2011). Seismic illumination is one key issue for subsurface imaging (Kim et al ., 2018) and reservoir characterization (Zambrini et al ., 2020), but the subsalt targets usually suffer from the problem of poor illumination (Liu et al ., 2011; Um et al ., 2014). The oil and gas industry has made great strides over the past two decades, but some fundamental challenges – such as imaging of poorly illuminated subsalt structures and complex salt interpretation – have not been entirely overcome (Etgen et al ., 2016).…”