Comparisons of Three Feedback Internal Multiple Elimination Methods

Internal multiples have posed a great challenge for current seismic imaging and inversion methods. One important family of internal multiple elimination (IME) methods is the layer-related, data-driven process based on the feedback model. For this kind of IME methods, virtual depth levels need to be selected in between strong reflecting interfaces and internal multiples related to these depth levels are addressed in a layer-stripping manner. In this paper, two IME methods based on prediction and subtraction together with one recently developed inversion-based IME method are reviewed and compared. Synthetic data and field data examples demonstrate that with adaptive subtraction avoided, the inversion-based IME can provide less multiple leakage and a better primary contrast.