Adaptive source deghosting in the common-shot domain

Common-receiver gathers with a dense source sampling are well suited for source-side deghosting based on wavefield propagation. However, often sources are sparsely sampled, which introduces aliasing artifacts for source deghosting based on wavefield propagation. The common-shot domain is often denser sampled. However, in the common-shot domain the source-side ghost wavefield is no longer determined by the water only. Instead, it will be affected by the complexity of the subsurface. Therefore, a data-driven estimation of the effect of the subsurface on the source ghost wavefield is integrated into our deghosting algorithm. The algorithm is based on wave field propagation operators that take into account the effect of the subsurface on the source-side ghost wavefield. To handle the effect of the subsurface on the source-side ghost wavefield, which is depth dependent, a multi-window implementation is used. A field data example is provided to demonstrate that source-deghosting in a well-sampled common-receiver domain gives an accurate ghost-free result. Then a comparison of the source-side ghost wavefield in the common-shot domain is made for two models: the Marmousi model (complex) and a horizontally layered model (simple). The source-side ghost wavefield is affected by the complex model, whereas the source-side ghost wavefield is unaffected by the simple model. The deghosting algorithm that takes into account the effect of the subsurface results in a more accurate deghosting result for the complex model compared to the deghosting algorithm that neglects the effect of the subsurface.