LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Global optimization strategies for implementing 3D CRS stack using the VFSA algorithm: Application to real land data

Photo by thomasw from unsplash

The three-dimensional common-reflection-surface (CRS) stack operator depends on eight kinematic wavefield attributes that must be extracted from the pre-stack data. These attributes are obtained by an efficient optimization strategy based… Click to show full abstract

The three-dimensional common-reflection-surface (CRS) stack operator depends on eight kinematic wavefield attributes that must be extracted from the pre-stack data. These attributes are obtained by an efficient optimization strategy based on the maximization of the coherence measure of the seismic reflection events included by the CRS stacking operator. The main application of these kinematic attributes is to simulate zero-offset stacked data; however, they can also be used for regularization of the pre-stack data, pre-stack migration, and velocity model determination. The initial implementations of the three-dimensional CRS stack used grid-search techniques to determine the attributes in several steps with the drawback that accumulated errors could deteriorate the final result. In this work, the global optimization Very Fast Simulated Annealing algorithm is used to search for the kinematic attributes by applying three optimization strategies for implementing CRS stacking: (a) simultaneous global search o...

Keywords: optimization strategies; stack; global optimization; strategies implementing; crs stack; optimization

Journal Title: Geophysics
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.