Risto Siliqi

Kinematic invariants: an efficient and flexible approach for velocity model building

We present a fast turnaround strategy for building depth velocity models from kinematic invariants. Our approach is based on the concept of kinematic invariants describing locally coherent events by their position and slopes in the un-migrated pre-stack domain. 3D slope tomography can be based on kinematic invariants that fully characterize the events in terms of positioning and focusing. Kinematic invariants offer a versatile tool for velocity model building as they can be derived from dip and move-out picks made either in pre-stack depth migrated (preSDM) or pre-stack time migrated (preSTM) domains, or even in the unmigrated domain. Since the invariants are in the unmigrated domain, they only need to be picked once. The classical iterative velocity update made of several iterations of RMO picking, pre-stack migration and velocity update can thus be replaced by a more efficient sequential approach involving a single preSDM and a single residual move-out (RMO) picking followed by a non-linear tomographic inversion, should the quality of the initial PreSDM be appropriate for an automated volumetric picking.

Structurally coherent wide azimuth residual move out surfaces

The inspection of the alignment of reflections on prestack image gathers is considered an excellent measure of the validity of the migration model. Moreover, it provides crucial information necessary to the prestack tomography update of the velocity model. A strong methodology is already established in the case of conventional narrow azimuth acquisition. However pre-stack depth imaging of wide azimuth surface seismic data (WAZ) with the introduction of 3D Common Image Gather (CIG) requires an appropriate automatic extraction of Residual Move Out signatures (RMO). By introducing an orthogonal decomposition of RMO kinematics using 2D functions we preserve any complexity related to large incidence angles and moreover allow azimuthal variations of RMO surfaces.