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dc.date.accessioned2020-06-04T18:52:18Z
dc.date.available2021-07-02T22:45:44Z
dc.date.created2019-09-17T14:15:48Z
dc.date.issued2019
dc.identifier.citationRäss, Ludovic Kolyukhin, Dmitriy Minakov, Alexander . Efficient parallel random field generator for large 3-D geophysical problems. Computers & Geosciences. 2019, 131, 158-169
dc.identifier.urihttp://hdl.handle.net/10852/76650
dc.description.abstractWe present an efficient implementation of the method for sampling spatial realisations of a 3-D random fields with given power spectrum. The method allows for a multi-scale resolution and approaches well for parallel implementations, overcoming the physical limitation of computer memory when dealing with large 3-D problems. We implement the random field generator to execute on graphical processing units (GPU) using the CUDA C programming language. We compare the memory footprint and the wall-time of our implementation to FFT-based solutions. We illustrate the efficiency of the proposed numerical method using examples of an acoustic scattering problem which can be encountered both in controlled-source and earthquake seismology. In particular, we apply our method to study the scattering of seismic waves in 3-D anisotropic random media with a particular focus on P-wave coda observations and seismic monitoring of hydrocarbon reservoirs.
dc.languageEN
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.titleEfficient parallel random field generator for large 3-D geophysical problems
dc.typeJournal article
dc.creator.authorRäss, Ludovic
dc.creator.authorKolyukhin, Dmitriy
dc.creator.authorMinakov, Alexander
cristin.unitcode185,15,22,40
cristin.unitnameSenter for Jordens utvikling og dynamikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1
dc.identifier.cristin1725718
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Computers & Geosciences&rft.volume=131&rft.spage=158&rft.date=2019
dc.identifier.jtitleComputers & Geosciences
dc.identifier.volume131
dc.identifier.startpage158
dc.identifier.endpage169
dc.identifier.doihttps://doi.org/10.1016/j.cageo.2019.06.007
dc.identifier.urnURN:NBN:no-79750
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn0098-3004
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/76650/2/GRFS_CAGEO_Rev4_draft.pdf
dc.type.versionAcceptedVersion
dc.relation.projectNFR/223272


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Attribution-NonCommercial-NoDerivatives 4.0 International
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