English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The emergence of long-offset sparse stationary-recording surveys carried outwith ocean bottom nodes (OBN) makes frequency-domain full waveform inversion(FWI) attractive to manage compact volume of data and perform attenuationimaging. One challenge of frequency-domain FWI is the forward problem, whichrequires the solution of large and sparse linear systems with multipleright-hand sides. While direct methods are suitable for dense acquisitions andproblems involving less than 100 million unknowns, iterative solver are moresuitable for large computational domains covered by sparse OBN surveys. Here,we solve these linear systems with a Krylov subspace method preconditioned withthe two-level Optimized Restricted Additive Schwarz (ORAS) domain decompositionpreconditioner, the prefix optimized referring to the use of absorbingconditions at the subdomain interfaces. We implement this method with finitedifferences on uniform grid and finite elements on unstructured tetrahedralmeshes. A simulation in a model where the velocity linearly increases withdepth allows us to validate the accuracy of the two schemes against ananalytical solution while highlighting how their relative cost varies with theband of propagated wavelengths. A simulation in the overthrust model involvingup to 2 billions of parameters allows us to tune the method and highlights itsscalability.

Large-scale finite-difference and finite-element frequency-domain seismic wave modelling with multi-level domain-decomposition preconditioner