Internal multiple attenuation based on inverse scattering: theoretical review and implementation in synthetic data

Melissa Judith Hernandez Quijada, Kristopher A. Innanen

Multiple reflections represent a serious problem in the field of seismic processing. Multiple events can be mistaken for primary reflections, and may distort primary events and obscure the task of interpretation. In this work we will focus in the suppression of internal multiples and we will illustrate how the inverse scattering internal multiple algorithm introduced by Weglein and Araujo in 1994, is capable to attenuate internal multiples without any a priori information about the medium through which the waves propagate. One of the advantages of this method over other methods is its ability in principle to suppress multiples that interfere with primaries without attenuating the primaries themselves. We consider the version of the algorithm for 1D normal incidence case. This algorithm predicts internal multiples from other events in the data by performing a convolution and a crosscorrelation of data. In this paper we review the algorithm in theory, discuss intuitively how it works, and examine the numerical behaviour of the algorithm in synthetic data. In particular, the role and importance of the algorithm parameter is emphasized. The findings of this work are put to use in prediction of internal multiples in physical model data (Hernandez, Innanen and Wong, 2011).