Paper Summary
High resolution tomographic inversion has conventionally been preceded by picking of 2nd and 4th order residual moveout of depth migrated gathers. However, this type of picking assumes that the residual moveout behaviour can adequately be characterised with a parametric fit of a simple curve to the form of moveout exhibited by the data. When we have small-scale velocity anomalies (with lateral extent a fraction of the acquisition spread length) this assumption breaks down. Unfortunately, picking the detailed non-parametric residual moveout behaviour can be very difficult, as the moveout trajectories can be obscured by residual noise (often remnant multiple), which can derail a non-parametric autopicker.
Here we demonstrate a successful implementation of non-parametric autopicking applied to two diverse data examples, and contrast the results with conventional tomographic inversion of parametrically picked moveout.