Stereotomography assisted by migration of attributes

Depth velocity model building remains a difficult step within the seismic depth imaging sequence. Stereotomography provides an efficient solution to this problem but was limited until now to a picking of seismic data in the prestack time un-migrated domain. We propose here a method for stereotomographic data picking in the depth migrated domain. Picking in the depth migrated domain exhibits the advantage of a better signal-to-noise ratio and of a more regular distribution of picked events in the model, leading to a better constrained tomographic inverse problem. Moreover, any improvement on the velocity model will improve the migrated results, again leading to improved picking. Our strategy for obtaining a stereotomographic dataset from a prestack depth migration is based on migration of attributes (and not on a kinematic demigration approach!). For any locally coherent event in the migrated image, migration of attributes allows one to compute ray parameter attributes corresponding to the specular reflection angle and dip. For application to stereotomography, the necessary attributes are the source/receiver locations, the traveltime and the data slopes. For the data slope, when the migration velocity model is erroneous, some additional corrections have to be applied to the result of migration of the attributes. Applying these corrections, our picking method is theoretically valid whatever the quality of the migration velocity model. We first present the theoretical aspects of the method and then validate it on 2D synthetic and real seismic reflection data sets.