Post-stack velocity analysis by separation and imaging of seismic diffractions

Introduction

Diffracted and reflected seismic waves are fundamentally different physical phenomena (Klem-Musatov, 1994). Most seismic data processing is tuned to imaging and enhancing reflected waves, which carry most of the information about subsurface. The value of diffracted waves, however, should not be underestimated (Khaidukov et al., 2004). When seismic exploration focuses on identifying small subsurface features (such as faults, fractures, channels, and rough edges of salt bodies) or small changes in seismic reflectivity (such as those caused by fluid presence or fluid flow during reservoir production), it is diffracted waves that contain the most valuable information.

In this paper, we develop an integrated approach for extracting and imaging of diffracted events. We start with stacked or zero-offset data as input and produce time-migrated images with separated and optimally focused diffracted waves as output. The output of our processing flow can be compared to coherence cubes (Marfurt et al., 1998; Bahorich and Farmer, 1995). While the coherence cube algorithm tries to enhance incoherent features, such as faults, in the migrated image domain, we perform the separation in unmigrated data, where these features appear in the form of diffracted waves.

We also introduce diffraction-event focusing as a criterion for migration velocity analysis, as opposed to the usual ``flat-gather'' criterion used in seismic imaging. Focusing analysis is applicable not only to multi-coverage prestack data but also to post-stack or single-coverage data.

The idea of extracting information from seismic diffractions is not new. Harlan et al. (1984) used forward modeling and local slant stacks for estimating velocities from diffractions; Landa and Keydar (1998) used common-diffraction-point sections for imaging of diffraction energy and detecting local heterogeneities; Soellner and Yang (2002) simulated diffraction responses for enhancing velocity analysis. Sava et al. (2005) incorporated diffraction imaging in wave-equation migration velocity analysis.

The novelty of our approach is in integration of two essential steps:

1. Separating diffracted and reflected events in the data space,
2. Focusing analysis for automatic detection of migration velocities optimal for imaging diffractions.

We explain both steps and illustrate their application with field and synthetic datasets.

Post-stack velocity analysis by separation and imaging of seismic diffractions