Analysis and application of data-driven approaches for internal-multiple elimination

Abstract

Imaging artifacts caused by strong internal multiples can interfere with primary images, affecting structural interpretation and amplitude analysis. In such cases, internal multiples are often attenuated in either data domain or in the image domain. In this abstract, we study three data-driven approaches: Jakubowicz, Inverse Scattering Series (ISS) and Marchenko for internal-multiple removal and analyze their performances. Each method has its unique advantages due to the differences among them. This knowledge, in turn, helps users to choose the appropriate method. Following the analysis, we show field data applications of these methods on towed steamer data.