Data-driven adaptive decomposition of multicomponent seabed seismic recordings; application to shallow-water data from the North Sea

Exploiting the full potential of multicomponent seabed seismic recordings requires the decomposition of the recorded data into their upgoing and downgoing P- and S-wave constituents. We present a case study from the North Sea, where a novel adaptive wave-equation-based decomposition method is applied to a 2D data set shot inline with a cable-based seabed seismic acquisition system. The data were recorded in relatively shallow ( approximately 150 m water, such that severe interference exists between primary reflections and water-layer multiples. Such conditions represent a challenge for many decomposition methods, because these often require a significant amount of interpretive, user-defined input. Conversely, the adaptive algorithm demonstrated in this study is fully data-driven, requiring as sole input a rough estimate of the water depth. The importance of careful mutual calibration of the sensors is demonstrated by critically assessing the properties of the derived calibration filters and the resulting estimates of the elastic properties of the seabed. To assess the effectiveness of the decomposition procedure, we compare a number of key events identified in the unprocessed data with their equivalents in the decomposed wavefields. The results of this case study show that the noninteractive decomposition method, which was demonstrated on seabed seismic data acquired in deep ( approximately 370 m) water, can be applied successfully in shallower conditions without further modification.