Suppression of dipping noise and multiples using 3D pre-stack time migration

Abstract

Conventional imaging of seismic data includes an approximate NMO and DMO prior to velocity analysis. The NMO and DMO imaging steps are approximate only in the sense that an approximate (simple) velocity field is used; the algorithms themselves are accurate. After velocity analysis, NMO is re-applied with the more detailed velocity field derived from the analyses. In the constant velocity case, DMO is almost independent of velocity and the iterative procedure described above plus post-stack migration yields an accurate image. The derived velocities may also be used for multiple suppression. Also, DMO itself may change the stacking velocities of dipping noise in such a way as to suppress the noise. An improved approach to velocity estimation and imaging is to apply the conventional approximate NMO and DMO and then also to apply an approximate zero-offset time migration to each common offset dataset prior to velocity analysis (3D MOVES). After velocity analysis, the NMO is re-applied and the data stacked. Post stack, either a residual migration or full diffraction plus full time or depth migration is applied. The pre-stack migration is either a constant velocity or single function v(z) algorithm. This is consistent with the NMO, DMO approach of accurate algorithms in an approximate velocity field. The algorithms are fast and can be inverted post stack to allow depth migration. The technique has been extensively used in 2D and 3D for imaging primaries and yielding accurate velocities. However, as with DMO, the derived velocity field may also be used for multiple suppression and the migration process may itself attenuate noise and multiples. For example, multiple diffractions may be focused and then attenuated in the stack process or with standard de-multiple methods. Alternatively, dipping noise and multiples may be migrated up dip and be located above the NMO mute pattern at middle and far offsets; the subsequent NMO, mute and stack remove the multiples from the data. In these applications, the migration process should be viewed as a transformation rather than an imaging tool, and the velocity used for migration need not be geologically correct, i.e. the velocity is a transformation parameter which is tuned to obtain the optimum noise suppression. Optimal imaging is obtained with residual, post-stack migration.