dc.date.accessioned | 2020-06-04T18:52:18Z | |
dc.date.available | 2021-07-02T22:45:44Z | |
dc.date.created | 2019-09-17T14:15:48Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Räss, Ludovic Kolyukhin, Dmitriy Minakov, Alexander . Efficient parallel random field generator for large 3-D geophysical problems. Computers & Geosciences. 2019, 131, 158-169 | |
dc.identifier.uri | http://hdl.handle.net/10852/76650 | |
dc.description.abstract | We 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.language | EN | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.title | Efficient parallel random field generator for large 3-D geophysical problems | |
dc.type | Journal article | |
dc.creator.author | Räss, Ludovic | |
dc.creator.author | Kolyukhin, Dmitriy | |
dc.creator.author | Minakov, Alexander | |
cristin.unitcode | 185,15,22,40 | |
cristin.unitname | Senter for Jordens utvikling og dynamikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |
dc.identifier.cristin | 1725718 | |
dc.identifier.bibliographiccitation | info: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.jtitle | Computers & Geosciences | |
dc.identifier.volume | 131 | |
dc.identifier.startpage | 158 | |
dc.identifier.endpage | 169 | |
dc.identifier.doi | https://doi.org/10.1016/j.cageo.2019.06.007 | |
dc.identifier.urn | URN:NBN:no-79750 | |
dc.type.document | Tidsskriftartikkel | |
dc.type.peerreviewed | Peer reviewed | |
dc.source.issn | 0098-3004 | |
dc.identifier.fulltext | Fulltext https://www.duo.uio.no/bitstream/handle/10852/76650/2/GRFS_CAGEO_Rev4_draft.pdf | |
dc.type.version | AcceptedVersion | |
dc.relation.project | NFR/223272 | |