Selective-input adaptation of model-based water-layer demultiple

Model-based water-layer demultiple (MWD) is an effective method for attenuating water-layer-related multiples (WLRMs), especially in shallow water environments. Regular 3D MWD use regularized common-offset cubes for both shot- and receiver-side multiples. We propose a selective-input adaptation of the regular 3D MWD workflow that uses both regularized shot gathers and regularized cubes as input and prioritizing the data selected for model prediction; data is first selected from regularized shot gathers and then regularized cubes. We demonstrate with field data that this selective-input MWD works better than regular MWD, especially for high-order multiple reverberations.