G. Gierse, J. Pruessmann, E. Laggiard, C. Boennemann, and H. Meyer show how the Common Reflection Surface (CRS) imaging technique developed by German research and commercial organizations can be successfully applied to a 3D dataset, in this case from a seismic survey off Costa Rica. The macro model independent Common Reflection Surface (CRS) imaging technique has proved to produce superior images in various 2D seismic case studies. A 3D marine dataset application demonstrates similar capabilities of the CRS technique for 3D data. The signal-to-noise ratio is strongly increased and dipping features are better resolved. The marine dataset is selected from the active continental margin offshore Costa Rica. The CRS processing aims at enhancing the image of the slope sediments and deeper crustal structures. The resolution of complex subsurface structures in 2D and 3D still represents a major challenge to seismic exploration. Up to now, continuous efforts have been made throughout the oil and gas industry to improve the imaging of complex structures with the main focus on prestack depth imaging. The seismic wavefront that travels through the complex subsurface is likely to deviate from a spherical shape having passed all sorts of inhomogeneities. Prestack depth migration has the advantage of not assuming a spherical wavefront like conventional techniques, since it calculates the actual deformations of the wavefront from a more or less coarse model of the subsurface. The derivation of the model, however, is a crucial step where prestack depth migration might fail. A very low signal-to-noise ratio in the seismic data often prevents the definition of a reliable basic model and the identification of the main horizons in the prestack data. Likewise, model building can fail in areas of complex tectonics, such as overthrust areas. Thus the strength of the model-based imaging cannot be exploited. For such cases, recent advances in time domain imaging with the CRS technique can be an alternative. CRS processing strongly increases the signal-to-noise ratio, and produces a significant improvement of imaging results. Poststack depth migration allows the transfer of the improved resolution from time domain to depth. In general, time processing has seen fewer efforts to improve the imaging techniques compared with depth processing. In many exploration projects, the conventional NMO / DMO processing flow for producing the zero-offset stack still dominates seismic processing in the time domain. This standard technique has prevailed nearly unchanged throughout the seismic industry during the last two decades. NMO / DMO processing uses a type of a macro model given by the stacking velocity field, which is derived from Common Midpoint (CMP) gathers. The velocity field describes the CMP reflection time curves, which are assumed to be hyperbolic. This assumption corresponds to undisturbed wavefronts from reflection points in a subsurface with plane horizontal layering. In case of dipping layers, the one dimensional subsurface model in the NMO approach leads to reflection point smearing, and requires a partial migration via the Dip Moveout (DMO) correction. Time domain imaging approaches, that were considered alternatives to the established NMO / DMO technique with its simplified subsurface model, have frequently been proposed. At the end of the 80s, de Bazelaire (1986, 1988) and Gelchinsky (1988, 1989) proposed new strategies for a zero-offset imaging. In contrast to the NMO/DMO technique, as well as prestack depth migration, these strategies do not require a macro model, but estimate the imaging parameters directly from the prestack data.