The influence of multiples and imaging approximations on focusing-effect AVA detection and removal

Ioan Vlad

nick@sep.stanford.edu

ABSTRACT

Focusing-effect AVA (FEAVA) consists of anomalous amplitudes due to transmission effects. In multiple-free synthetic datasets, whether simple or complex, the focusing is removed by migration with the correct velocity and an operator adjoint to that used in modeling. In multiple-affected synthetic datasets, migration with the correct velocity but with an operator less accurate than that used in modeling is only partially sucessful in removing FEAVA. There are numerical experiments which can distinguish whether this is due to the presence of multiples, to lack of imaging operator accuracy, or to lack of imaging-modeling adjointness.