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Least-squares RTM: Reality and possibilities for subsalt imaging

We investigated how current least-squares reverse time migration (LSRTM) methods perform on subsalt images. First, we compared the formulation of data-domain vs. image-domain least-squares migration (LSM), as well as methods using single-iteration approximation vs. iterative inversion. Next, we examined the resulting subsalt images of several LSRTM methods applied on both synthetic and field data. Among our tests, we found image-domain single-iteration LSRTM methods, including an extension from Guitton’s (2004) method in the curvelet domain, not only compensated for amplitude loss due to poor illumination caused by complex salt bodies, but also produced subsalt images with fewer migration artifacts (i.e., noise) in the field data. By contrast, an iterative inversion method showed its potential for broadening bandwidth in the subsalt, but was less effective in reducing noise. Based on our understanding, we will summarize the current state of LSRTM for subsalt imaging, especially between single-iteration and iterative LSRTM methods.

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Joint inversion of velocity and density in preserved amplitude full waveform inversion

The importance of inverting jointly velocity and density parameters in full waveform inversion (FWI) is well established. In a former work we had proposed an innovative preserved amplitude FWI allowing improving the convergence rate of FWI. It was derived from preserved amplitude reverse time migration (RTM), involved a deconvolution imaging condition and was limited to the estimation of velocity perturbation from reflection data. We extend here the approach to a joint velocity and density preserved amplitude FWI. We present the theoretical derivation of the improved common shot FWI gradients and show how we can decouple the two parameters. We validate our approach on the Marmousi II synthetic model which shows that we can efficiently reconstruct the two parameters, and on a real data showing that we significantly reduce the data residual with the joint inversion.

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AVA compliant prestack spectral enhancement

Spectral broadening of migrated and stacked seismic images is a common method to enhance interpretability of reflection data. In this paper we propose a prestack AVA compliant spectral broadening approach based on non-stationary wavelet deconvolution. The algorithm employs AVA coupling in the prestack domain to shape the spectra of all traces in angle gathers simultaneously. Using synthetic and real data we show that the characteristics of all AVA classes are preserved and that the spectra of all angles are enhanced and better balanced.

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An alternative to least-squares imaging using data-domain matching filters

Posing migration as an inverse or a least-squares problem can improve the quality of imaging. This class of techniques can resolve illumination issues and improve focusing. Standard iterative least-squares imaging can be expensive and results are often compromised. We present a procedure using matching filters operating in data-space rather than image space. Effective inversion results are demonstrated on synthetic and real data.

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Reverse Time Migration of Multiples: Applications and Challenges

Marine seismic acquisitions record both primary and multiple wavefields. In a typical processing sequence, multiple energy is removed from the data before migration. However, there may be valuable information contained in the multiple wavefield. To discover this hidden information, reverse time migration of multiples (RTMM) was proposed. We evaluated the advantages of RTMM through three different real data processing projects and identified three key advantages. Additionally, we present a synthetic study of two types of crosstalk noise that hinder the full potential of RTMM as well as propose corresponding practical strategies to handle them.

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