Seismic image texture enhancement denoising using fractional time integral and diffusion tensor
Qingbao Zhou, Jinghuai Gao, LI Ke-xue · 2013
In this paper, we propose a new approach devoted to the denoising and the enhancing of strongly oriented seismic image. The approach is based on diffusion tensor and fractional time integral which can be written as a Volterra matrix-valued equation when our method applies to seismic image. Since the fractional integral equation interpolates a linear parabolic equation and a hyperbolic equation, the solution enjoys intermediate properties. The Volterra equation introduced is well-posed for all time t > 0. Since the seismic image shows the typical line-like texture character, diffusion tensor is introduced to analysis such features. In contrast to many other nonlinear diffusion techniques, such as scalar diffusivity, diffusion tensor allows real anisotropic behavior. The preferred diffusion direction is determined according to the eigenvectors of the structure tensor, and the diffusivity in this direction is controlled by the eigenvalues. The coherent seismic events and some important geology structures reflected by them can be preserved and enhanced in our framework. The improvements achieved by our approach are illustrated with real seismic data experiments.