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Abstract

Summary

Several recent studies have established that seismic full-waveform inversion (FWI) can be used to generate interpretable models of acoustic reflectivity from practically raw seismic data. Owing to their use of the full wavefield and an iterative least-squares approach to optimisation, these models, referred to as FWI images, offer an improvement in image quality over conventional approaches to depth migration, such as Kirchhoff pre-stack depth migration. Furthermore, the ability of FWI – when combined with an appropriate objective function – to begin from a basic initial model and unprocessed data means that these images can begin to be built shortly after acquisition. The effectively limitless scale of public cloud compute allows for these workloads to then be turned around quickly, while reasonable costs can be maintained by leveraging spare capacity markets. In an exploration setting, the availability of high-quality FWI images soon after acquisition can aid in improved and faster decision-making. In this abstract, we demonstrate our proposed workflow using a large subset of a modern surface-streamer dataset that was recently acquired for exploration purposes. 45 and 60 Hz FWI images were generated within weeks of the survey concluding and prior to a conventional fast-track image being delivered.

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/content/papers/10.3997/2214-4609.202210580
2022-06-06
2024-03-29
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References

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