Marchenko Redatuming and Imaging by Multidimensional Deconvolution (MDD)

Abstract

Summary In seismic imaging, using reflection data, the main goal is to obtain an image of the subsurface. Based on the Marchenko equations we have a scheme that allows us to retrieve the Green’s functions for any given set of points, if reflection data and a background velocity field are provided. Consequently, it is possible to target specific areas for imaging. The main advantage of the Marchenko imaging method is that it can efficiently remove multiple events. After computing the up- and downgoing Green’s functions, to build an image it’s necessary to choose which imaging condition procedure will be applied. About that, this work will discuss four image conditions. We also will discuss the most important aspects of the implementation of the MDD imaging condition, commenting on the details applied to this type of imaging condition using a least-squares method. We use a synclinal model and compare its Marchenko image with a RTM image. We observed that the Marchenko images are clean and of good quality. MDD provided the best results, but at a higher computational cost.