Application of Iterative Least-Squares Migration in Different Geological Settings

Korsmo, Ø.; Arasanipalai, S.; Greplowski, Z.; Farouki, Mazin

doi:10.3997/2214-4609.201901188

Cited by 2 publications

(1 citation statement)

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“…Different implementations of LSM exist in both the image and data space, with curvelet domain matching filters, Point Spread Functions (PSFs) and the full iterative LSM (Guitton, 2004;Valenciano, 2008;Lu et al, 2017). Existing solutions include both ray-based and wave-theoretic migrations (Korsmo et al, 2019(Korsmo et al, , 2021. A fundamental requirement is that the velocity model is assumed to be known and unchanged during the inversion.…”

Section: Methodsmentioning

confidence: 99%

Nonlinear LS-RTM based on the seismic scale separation and full-wavefield multiparameter FWI

Korsmo

Yang

Chemingui

et al. 2022

Second International Meeting for Applied Geoscience &Amp; Energy

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Least-squares migration (LSM) images the subsurface through an inversion process and seeks the reflectivity model that best explains the measured data. This data-fitting process will implicitly compensate for wavefield propagation effects and limited resolution seen with conventional imaging. These favourable properties have made it the method of choice in complex geological settings.In this paper, we will discuss the various properties and implementations of LSM and Full Waveform Inversion (FWI) and suggest a new nonlinear least-squares reverse time migration (LS-RTM) implemented in the framework of FWI. The new inversion estimates the earth reflectivity while updating the velocity model at every iteration. We demonstrate the new solution on a field data example from the Norwegian Sea.

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