Three‐dimensional Marchenko internal multiple attenuation on narrow azimuth streamer data of the Santos Basin, Brazil

Abstract

In recent years, a variety of Marchenko methods for the attenuation of internal multiples has been developed. These methods have been extensively tested on two‐dimensional synthetic data and applied to two‐dimensional field data, but only little is known about their behaviour on three‐dimensional synthetic data and three‐dimensional field data. Particularly, it is not known whether Marchenko methods are sufficiently robust for sparse acquisition geometries that are found in practice. Therefore, we start by performing a series of synthetic tests to identify the key acquisition parameters and limitations that affect the result of three‐dimensional Marchenko internal multiple prediction and subtraction using an adaptive double‐focusing method. Based on these tests, we define an interpolation strategy and use it for the field data application. Starting from a wide azimuth dense grid of sources and receivers, a series of decimation tests are performed until a narrow azimuth streamer geometry remains. We evaluate the effect of the removal of sail lines, near offsets, far offsets and outer cables on the result of the adaptive double‐focusing method. These tests show that our method is most sensitive to the limited aperture in the crossline direction and the sail line spacing when applying it to synthetic narrow azimuth streamer data. The sail line spacing can be interpolated, but the aperture in the crossline direction is a limitation of the acquisition. Next, we apply the adaptive Marchenko double‐focusing method to the narrow azimuth streamer field data from the Santos Basin, Brazil. Internal multiples are predicted and adaptively subtracted, thereby improving the geological interpretation of the target area. These results imply that our adaptive double‐focusing method is sufficiently robust for the application to three‐dimensional field data, although the key acquisition parameters and limitations will naturally differ in other geological settings and for other types of acquisition.

An open-source framework for the implementation of large-scale integral operators with flexible, modern high-performance computing solutions: Enabling 3D Marchenko imaging by least-squares inversion

“…The solution of the Marchenko equations for 3D datasets has so far been limited to the Neumann-type iterative scheme Jia et al, 2018b;Lomas and Curtis, 2019;Brackenho↵ et al, 2020;Staring and Wapenaar, 2020). In this paper we present the first 3D example of Marchenko redatuming where the solution is obtained using a gradient-based solver.…”

“…Finally, other challenges specific to the solution of the Marchenko equations such as knowledge and deconvolution of the source wavelet and removal of free-surface multiples are inherently similar to both 2D and 3D applications. Several solutions have been proposed in previous field data applications, both in terms of data pre-processing (Ravasi, 2019;Jia et al, 2018a;Staring et al, 2018;Mildner et al, 2019;Staring and Wapenaar, 2020), as well as modification of the underlying redatuming scheme (Ravasi, 2017;Slob and Wapenaar, 2017;Vargas et al, 2021) which could be directly applied in a 3D context. Perhaps more poorly understood right now is the impact of attenuation on the solution of the Marchenko equations (Slob, 2016): whilst simple amplitude-based data compensations have proven su cient so far in 2D field data application, the e↵ect of attenuation on the solution of the 3D Marchenko equations requires additional studies and will be subject of future research.…”

Marchenko redatuming, imaging, and multiple elimination and their mutual relations

“…We emphasize that an adaptive implementation is only needed to compensate for imperfections in the reflection response and for attenuation but not for limitations of the theory. Field data applications of this method (2D and 3D) are presented by Staring et al (2018) and Staring and Wapenaar (2020).…”

Unified elimination of 1D acoustic multiple reflection

“…The effect of line data on 2D methods and out‐of‐plane effects as well as sampling conditions for three‐dimensional (3D) applications have been analysed (Jia et al ., 2019; Lomas and Curtis, 2020). A 3D example of approximate double focusing can be found in Staring and Wapenaar (2020). Review, comparison and introductory publications on Marchenko redatuming and imaging are available in the literature (Wapenaar et al ., 2017; Nowack and Kiraz, 2018; Lomas and Curtis, 2019).…”