The goal in this study was to create and implement an AVA analysis algorithm that effectively identified Class III AVO sands. From the synthetic and real data cases, it is clear that our algorithm can select parts of the image corresponding to Class III AVO anomalies. However, it is also clear that a multiple suppression technique must be used in order to make our AVA algorithm effective in complex settings. Even then, the scattering effect of sharp velocity contrasts can inhibit good AVA analysis.
It is important to realize that seismic attributes, such as amplitude, hold a lot of information about rock properties. However, amplitudes can be altered significantly throughout the course of seismic processing. With this in mind, AVA data should be used carefully, as an aid to interpretation, rather than a direct hydrocarbon indicator.