Multiple events can be mistaken for primary reflections, and may distort primary events and obscure the task of interpretation (Hernandez, and Innanen, 2011). So, to eliminate these effects, internal multiple prediction becomes a necessity in the industry. In this paper, we determine the definitions of primaries, multiples, and the most important concept in this research, internal multiples. Inverse scattering series will be introduced here. Then we review the basic principles of 1D and 2D internal multiple prediction algorithm, which were introduced to geophysics literature in the 1990s (Araujo et al., 1994; Weglein et al., 1997, 2003), and demonstrate 1D algorithm's use to 1D synthetic data using a MATLAB implementation. Also the basic idea of a lower-higher-lower relationship will be discussed. Then the role and importance of the parameter . are emphasized and the effects of badly chosen epsilon values are shown. The 1D internal multiple algorithm has been tested with good results on band-limited synthetic data. Analytical and numerical examples will be used to exemplify the usefulness of 1D internal multiple prediction algorithm.
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