3D diffraction imaging attributes and their application for fault and fracture localization and characterization

Abstract

We present a 3D diffraction imaging procedure with the subsequent computation of diffraction attributes and their application in field seismic data processing. This procedure consists of a weighted asymmetric summation of 3D seismic data based on Gaussian beams double-focusing. The different mutual geometry of beams produces 3D selective diffraction images concerning scattering azimuth representing the target objects, such as fractures, faults, and caverns. We introduce three diffraction attributes based on 3D selective images: structural diffraction attribute, point diffraction attribute, and the azimuth of structural diffraction. Compared with the conventional diffraction energy, these attributes open the possibility of distinguishing between fractured and cavernous objects and determining the orientations of fractures and faults. Compared with the other diffraction attributes, the proposed attributes result from the analysis of the diffracted wave behavior in 3D media and are not typical image processing algorithms.We evaluate the approach using synthetic and real data sets containing canonical features like faults, caves, and fracture corridors that generate diffractions.