Revisiting two notable methods for improving the deblending performance of marine towed-streamer acquisition

Abstract

Marine towed-streamer blended data are usually challenging to deblend because of the low dimensionality of the data. While the present ocean-bottom-cable (OBC) surveys produce well-sampled 3D receiver gathers, towed-streamer data have a lower sparsity in the transformed f - k domain. Here, we revisit two practical strategies to improve deblending performance. In the first strategy, we revisit applying 3D deblending to 2D surveys, which considers the shot domain as a sparsity-constrained domain. We compare the sparseness of the 2D and 3D FFT transformed domains by drawing the coefficients’ decaying curves. The 3D FFT transformed domain is much sparser than the 2D FFT transformed domain, according to the sparseness comparison. Thus, 3D deblending can obtain better performance than 2D deblending. In the second strategy, we revisit an improved deblending approach that combines traditional deblending and popcorn reconstruction, and other methods of coding sources. The popcorn shooting technique adds an extra level of constraint to the inversion because each source is coded with a different popcorn pattern. Thus, when deblending, convolution and deconvolution for each source with a predefined popcorn pattern will attenuate the interference that does not belong to the selected source. For both scenarios revisited here, we use both synthetic and field data examples with different complexity to demonstrate their superior performance.