Adaptive multiple subtraction with a pattern‐based technique

Abstract

Surface-related multiple elimination(SRME) (Berkhout, 1982; Verschuur et al, 1992) has been an effective algorithm to remove multiples that are difficult to eliminate using other conventional algorithms. SRME has two steps. The first step is multiple prediction, and the second step is multiple adaptive subtraction. In the first step, the multiple model is constructed by 2D convolutions of the seismic data without knowledge of the subsurface structures, and it can handle complex structures. In reality, however, variations in the acquisition wavelet, cable feathering, dip in crossline direction, boundary effect, limited offset range can introduce time shifts or amplitude artifacts into the predicted multiples. Consequently, there are discrepancies between the real multiples and the predicted multiples. The second step takes them into account. Conventional method to do this is to apply a matching filter in t-x domain to the predicted multiples, and then subtract the match-filtered multiples from the seismic data. This matching filter is calculated by a least squares algorithm. Unfortunately, when multiples strongly interfere with primaries, these methods give biased primaries after subtraction.