Improving depth imaging of legacy seismic data using curvelet-based gather conditioning: A case study from Central Poland

•Case study of applying pre-stack depth migration to vintage data•New curvelet-based scheme for conditioning pre-stack gather is presented•Improved velocity model building workflow

In presented work we test the ray-based pre-stack depth migration (PreSDM) and tomographic velocity model building (VMB) workflow applied to vintage seismic data, acquired in the 70s and 80s, in the area affected by intense salt tectonics in Central Poland. We demonstrate that the key for successful VMB is the consistency of the input residual moveouts (RMO) picks, which we obtain by developing proper gather conditioning workflow. It is based on the 2D discrete curvelet transform (DCT). DCT-based conditioning algorithm is run in a two-step mode on the common offset sections and on the depth-slices, improving the performance of the autopicker and thus providing a more reliable input to a grid tomography. Additionally, in the case of the legacy data, such conditioning acts as a trace regularization. Taking into account limitations associated with low fold and low signal-to-noise ratio, obtained results are satisfactory, providing depth sections and velocity models for verifying structural interpretation of the study area. In the case when the grid-based tomography is applied to vintage data, we strongly recommend to devote some time for proper data conditioning aimed at signal coherency improvement before running the RMO autopicker.