Enabling wave-based inversion on GPUs with randomized trace estimation

TitleEnabling wave-based inversion on GPUs with randomized trace estimation
Publication TypeConference
Year of Publication2022
AuthorsMathias Louboutin, Felix J. Herrmann
Conference NameEAGE Annual Conference Proceedings
Month06
KeywordsEAGE, Image Volumes, inversion, RTM, SEAM, stochastic, TTI
Abstract

By building on recent advances in the use of randomized trace estimation to drastically reduce the memory footprint of adjoint-state methods, we present and validate an imaging approach that can be executed exclusively on accelerators. Results obtained on field-realistic synthetic datasets, which include salt and anisotropy, show that our method produces high-fidelity images. These findings open the enticing perspective of 3D wave-based inversion technology with a memory footprint that matches the hardware and that runs exclusively on clusters of GPUs without the undesirable need to offload certain tasks to CPUs.

Notes

(EAGE, Madrid)

URLhttps://slim.gatech.edu/Publications/Public/Conferences/EAGE/2022/louboutin2022eageewi/louboutinp.html
DOI10.3997/2214-4609.202210531
Presentation
Software
Citation Keylouboutin2022EAGEewi