Differential Semblance Optimization for 2D Velocity Field Estimation

The "flatness" of events in the Common Image Gathers (CIGs) used for AVO analysis, is directly related to the quality of the velocity model [4,6]. The method we present here for velocity estimation in 2D media is precisely adapted to further AVO analysis, as its aim is to flatten the depth migrated CIGs. For an automatic velocity estimation where no picking is introduced, the choice of the objective cost function which measures the "flatness" of the coherency panels, is crucial. We explore some proporties of the Differential Semblance function, introduced by [7], to prove its efficiency in 2D velocity estimation. Synthetic tests are presented here, and show that at least in these cases, total optimization algorithms may be applied.