1887

Abstract

Summary

To overcome the limitations of conventional Full Waveform Inversion methods for large-scale velocity updates from reflection data, the Reflection Full Waveform Inversion (RFWI) approach has been proposed. RFWI suffers from a slow convergence and potential artifacts related to inconsistencies when alternating background velocity model and reflectivity model updates. Furthermore, the estimation of the reflectivity based on a Reverse Time Migration (RTM) represents a substantial numerical cost in the RFWI workflow. To tackle these difficulties, the Time consistent Waveform Inversion (TWIN) method has been proposed. This method better accounts for the reflectivity-background velocity coupling effect and uses a numerically cheap shot-independent zero-offset migration operator. After summarizing the concept of TWIN, we present the first published real data application of the TWIN method (marine streamer dataset). Our inversion methodology is mainly data-driven and considers a very erroneous initial background velocity model. After 17 iterations, TWIN performs large velocity model updates up to 7 km depth. The inverted velocity model allows for a significant flattening of the RTM-offset gathers, and strong improvements of the RTM image in complex areas. Furthermore, even with a very large smoothing (8 km), we verify that the TWIN and RFWI gradients significantly differ.

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/content/papers/10.3997/2214-4609.202310585
2023-06-05
2026-01-21

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References

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/content/papers/10.3997/2214-4609.202310585
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An Application of the Time consistent Waveform INversion (TWIN) method to a marine dataset
Conference Proceedings 2023, 1 (2023); https://doi.org/10.3997/2214-4609.202310585
/content/papers/10.3997/2214-4609.202310585
/content/papers/10.3997/2214-4609.202310585
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