Common Reflection Surface (CRS) methods have become popular in the geophysical industry since the introduction of multi-parameter stacking operators in the 1990s. They were originally designed to replace DMO processing which just added the dip component into the underlaying NMO subsurface model. However, DMO processing was still lacking information about the subsurface curvature. The most generalized subsurface model including the wavefront attributes related to dip, depth and curvature of subsurface reflection elements is the basis of multi-parameter stacking operators such as the CRS operator. Gajewski (2019) discussed that those wavefront attributes are even accurate for complex media and can be used for many applications such as data regularization and interpolation, diffraction processing, wavefront tomography and even passive seismic imaging. This paper focuses on the application of wavefront attributes in depth imaging of complex subsurface data. A workflow will be presented that makes use of CRS partial stacking in order to create a dataset of regular shot and receiver locations for Reverse Time Migration (RTM). A hybrid approach to RTM depth model building will be introduced which makes use of a standard tomography approach for the good quality part of the data. RTM surface offset gathers are used for constant velocity migrations in the poor data quality part in order to create a velocity model where no residual moveout picks and thus no tomography is possible. RTM in combination with CRS allows for an improved imaging of rough topography & complex subsurface geology data where conventional approaches usually fail. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 8:30 AM Presentation Start Time: 8:30 AM Location: 214D Presentation Type: Oral