Correcting For Imperfectly Sampled Data in the Iterative Marchenko Scheme

Abstract

Summary The Marchenko method retrieves the responses to virtual sources in the subsurface, accounting for all orders of multiples. The method is based on two integral representations for focusing and Green's functions. In discretized form these integrals are represented by finite summations over the acquisition geometry. Consequently, the method requires ideal geometries of regularly sampled and co-located sources and receivers. However, a recent study showed that this restriction can, in theory, be relaxed by deconvolving the irregularly-sampled results with certain point spread functions (PSFs). The results are then reconstructed as if they were acquired using a perfect geometry. Here, the iterative Marchenko scheme is adapted in order to include these PSFs; thus, showing how imperfect sampling can be accounted for in practical situations. Next, the new methodology is tested on a 2D numerical example. The results show clear improvement between the proposed scheme and the standard iterative scheme. By removing the requirement for perfect geometries the Marchenko method can be more widely applied to field data.