GPU-accelerated Full-Waveform Inversion using Hamiltonian Monte Carlo Method

D. Urozayev; B. Boddupalli; P. Eliasson

doi:10.3997/2214-4609.2024636008

oa GPU-accelerated Full-Waveform Inversion using Hamiltonian Monte Carlo Method
Authors D. Urozayev¹, B. Boddupalli¹ and P. Eliasson¹
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¹ SINTEF AS
Publisher: European Association of Geoscientists & Engineers
Source: Conference Proceedings, Eighth EAGE High Performance Computing Workshop, Sep 2024, Volume 2024, p.1 - 3
DOI: https://doi.org/10.3997/2214-4609.2024636008

Abstract

Summary

This study utilizes GPU computing to perform seismic full waveform inversion, a high-dimensional and ill-posed problem. By employing hybrid Hamiltonian Monte Carlo methods, it enables efficient computation of the posterior distribution under various priors, which regularize the problem. The approach facilitates assessing the efficiency of different priors and regularization techniques. As high-performance computing continues to advance, these methods allow for the development of more sophisticated inversion algorithms for large-scale seismic problems, improving uncertainty estimation and aiding decision-making.

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2025-11-16

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References

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/content/papers/10.3997/2214-4609.2024636008

GPU-accelerated Full-Waveform Inversion using Hamiltonian Monte Carlo Method

Conference Proceedings 2024, 1 (2024); https://doi.org/10.3997/2214-4609.2024636008

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oa GPU-accelerated Full-Waveform Inversion using Hamiltonian Monte Carlo Method

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