Deblending of simultaneous source with rank reduction and thresholding constraints

In this paper, we propose an iterative method combining the rank-reduction and thresholding constraints, to separate the simultaneous source data. In the common receiver domain, the incoherent interference generated by simultaneous source acquisition increases the rank of the Hankel matrix. Thus, rank-reduction can effectively suppress the incoherent interference. When the rank is small, the incoherent interference can get well attenuated, but it will introduce unexpected artifacts. We use the threshold function further to attenuate the unexpected artifacts. In the next iteration, we enlarge the rank and reduce the threshold value. More accurate deblended results are then recovered. The proposed algorithm is tested via two synthetic and one field data examples.