Automatic V Elocity Estimation from Locally Coherent E V Ents Picked in the Depth Migrated Domain: Application on a 2d Real Data Set

We demonstrate a method for 2D velocity estimation on real data with no assumption on the re ector geometry nor on the unknown background velocity eld. In the prestack depth migrated volume, locally coherent events are automatically picked without interpretation and characterized by their positions and two slopes. The velocity is estimated by optimizing the atness of these events in the Common Image Gathers via ray tracing. We show the possibility of an e cient inversion on a 2D real data set using a local optimization algorithm and the migration of selected Common Image Gathers (CIGs) and Common O set Gathers (COGs).