ITERATIVE DEBLENDING BASED ON THE MODIFIED SINGULAR SPECTRUM ANALYSIS

Deblending of simultaneous-source seismic data aims at separating the blended records caused by simultaneous shooting as if the data are acquired traditionally. In this paper, we propose a novel modified singular spectrum analysis (SSA) approach to remove blending noise in an iterative inversion manner. Compared with the traditional SSA approach, the modified SSA approach applies a modified truncated singular value decomposition (TSVD) onto the Hankel matrix in the frequency domain, and can attenuate more blending noise than the traditional SSA method. We use both synthetic and field data examples to demonstrate that the proposed modified SSA method has a stronger signal-and-noise separability.