Source wavelet correction for practical Marchenko imaging: A sub‐salt field‐data example from the Gulf of Mexico

Abstract

Imaging a target zone below a salt body can be challenging because large velocity contrasts in the overburden between the salt and surrounding sediments generate internal multiples, which interfere with primary reflections from the target level in the imaging process. This can lead to an erroneous interpretation of reflections in the sub‐salt area if multiples are misinterpreted as primaries. The Marchenko redatuming method may enable imaging of the sub‐salt target area where the effect of the multiply‐scattering overburden is removed. This is achieved by creating a redatumed reflection response where virtual sources and receivers are located below the overburden using a macromodel of the velocity field and the surface reflection data. The accuracy of the redatumed data and the associated internal multiple removal, however, depends on the accurate knowledge of the source wavelet of the acquired reflection data. For the first time, we propose a method which can accurately and reliably correct the amplitudes of the reflection response in field data as required by the Marchenko method. Our method operates by iteratively and automatically updating the source function so as to cancel the most artefact energy in the focusing functions, which are also generated by the Marchenko method. We demonstrate the method on a synthetic dataset and successfully apply it to a field dataset acquired in a deep‐water salt environment in the Gulf of Mexico. After the successful source wavelet estimation for the field dataset, we create sub‐salt target‐oriented images with Marchenko redatumed data. Marchenko images using the proposed source wavelet estimation show clear improvements, such as increased continuity of reflectors, compared to surface‐based images and to conventional Marchenko images computed without the inverted source wavelet. Our improvements are corroborated by evidence in the literature and our own synthetic results.

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

“…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.…”

Scattering-based focusing for imaging in highly complex media from band-limited, multicomponent data

“…The idea of reproducing full wavefield responses from virtual sources at depth using focusing operators as presented in the previous section requires several key preprocessing steps that may introduce inaccuracies or even hinder the implementation of Marchenko redatuming in real data sets (Ravasi et al, 2016;da Costa Filho et al, 2017;Jia et al, 2018;Mildner et al, 2019a). The original approach demands knowledge of the acquisition wavelet and dense spatial distribution of sources and receivers.…”

Internal multiple elimination: Can we trust an acoustic approximation?

“…Attempts of marine field data applications still show seismic-like results, however, without offering any proof of correct multiple elimination (e.g. Ravasi et al, 2016;Jia et al, 2018;Mildner et al, 2019;Staring et al, 2020). Assessing the results can be challenging without a reference, especially, when multiples generate complex interference patterns dominated by specific frequencies.…”