Accurate diffraction imaging for detecting small-scale geologic discontinuities

Abstract

Seismic diffractions contain valuable information regarding small-scale inhomogeneities or discontinuities, and therefore they can be used for seismic interpretation in the exploitation of hydrocarbon reservoirs. Velocity analysis is a necessary step for accurate imaging of these diffractions. A new method for diffraction velocity analysis and imaging is proposed that uses an improved adaptive minimum variance beamforming technique. This method incorporates the minimum variance, coherence factor, and correlation properties to improve the signal-to-noise ratio and enhance correlations. Our method can make seismic diffractions become better focused in semblance panels, allowing for the optimal migration velocity for diffractions to be accurately picked. Synthetic and field examples demonstrate that the migration velocity for the diffractions can differ from that for the reflections. The results suggest that the diffraction velocity analysis and imaging method is feasible for accurately locating and identifying small-scale discontinuities, which leads to the possibility of using this approach for practical application and seismic interpretation.

Accurate Delimitation of Mine Goaves Using Multi-Attribute Comprehensive Identification and Data Fusion Technologies in 3D Seismic Exploration

“…Data processing is always based on high-resolution and high-fidelity processing technologies. The combination of all-round and multi-means processing technologies is the key to accurately determine the position of goaf boundaries [10,11].…”

Diffraction pattern recognition using deep semantic segmentation

“…Diffracted wavefield imaging has, in recent decades, grown and attracted special interest in seismic exploration because of its ability to provide detailed information on structural setting, heterogeneity, anisotropy and even lithological composition (e.g., Landa and Keydar, 1998;Malehmir and Bellefleur, 2009;Dell et al, 2013;Lin et al, 2018;Schwarz and Krawczyk, a diffraction can be difficult to directly imaging, particularly if it appears in fast media where the signal-to-noise ratio is low and the diffraction tails usually interfere with steep reflections. Most techniques developed for diffraction signal separations are based on well-established concepts such as planewave destruction filters adapted to suppress energy from the local plane waves (Fomel, 2002), coherent wavefield subtraction (Schwartz, 2019), which is based on the estimation of coherency of the reflection signal and its subtraction from the rest of the wavefield, and multi-focusing by coherent summation of diffractions followed by the suppression of reflection signal (e.g., Berkovitch et al, 2009).…”

“…Diffracted wavefield imaging has, in recent decades, grown and attracted special interest in seismic exploration because of its ability to provide detailed information on structural setting, heterogeneity, anisotropy and even lithological composition (e.g., Landa and Keydar, 1998; Malehmir and Bellefleur, 2009; Dell et al ., 2013; Lin et al ., 2018; Schwarz and Krawczyk, 2020). Diffraction imaging from ground‐penetrating radar (GPR) surveys is, however, often associated with the mapping of shallow geological structures and for utility detections among others (e.g., Dave and Annan, 1989; Grasmueck, 1996; Theune et al ., 2006; Grasmueck et al ., 2015; Yuan et al ., 2019).…”

Diffraction separation by variational mode decomposition

“…Recently, diffracted wavefields have gained much interest because of their advantages in imaging small‐scale geologic structures and many publications have focused on diffraction separation and imaging (e.g. Landa et al ., 1987; Klokov et al ., 2004; de Figueiredo et al ., 2013; Lin et al ., 2018a; Zhao et al ., 2019). Most scholars focus on separating diffracted wavefields from the full wavefields by utilizing the kinematic and dynamic differences of reflected and diffracted wavefields in the prestack or poststack domains.…”