{"title":"将简化物理模型与粗网格结合起来,加快棘手的三维时域模拟速度","authors":"Wouter Deleersnyder, Evert Slob","doi":"arxiv-2408.17137","DOIUrl":null,"url":null,"abstract":"Full 3D modelling of time-domain electromagnetic data requires tremendous\ncomputational resources. Consequently, simplified physics models prevail in\ngeophysics, using a much faster but approximate (1D) forward model. We propose\nto join the accuracy of a 1D simplified physics model with the flexibility of\ncoarse grids to reduce the modelling errors, thereby avoiding the full 3D\naccurate simulations. We exemplify our approach on airborne time-domain\nelectromagnetic data, comparing the modelling error with the standard 3%\nmeasurement noise. We find that the modelling error depends on the specific\nsubsurface model (electrical conductivity values, angle representing the\ndeviation of the 1D assumption) and the specific (temporal) discretization. In\nour example, the computation time is decreased by a factor of 27. Our approach\ncan offer an alternative for surrogate models, statistical relations derived\nfrom large 3D datasets, to replace the full 3D simulations.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Joining simplified physics models with coarse grids to speed-up intractable 3D time-domain simulations\",\"authors\":\"Wouter Deleersnyder, Evert Slob\",\"doi\":\"arxiv-2408.17137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Full 3D modelling of time-domain electromagnetic data requires tremendous\\ncomputational resources. Consequently, simplified physics models prevail in\\ngeophysics, using a much faster but approximate (1D) forward model. We propose\\nto join the accuracy of a 1D simplified physics model with the flexibility of\\ncoarse grids to reduce the modelling errors, thereby avoiding the full 3D\\naccurate simulations. We exemplify our approach on airborne time-domain\\nelectromagnetic data, comparing the modelling error with the standard 3%\\nmeasurement noise. We find that the modelling error depends on the specific\\nsubsurface model (electrical conductivity values, angle representing the\\ndeviation of the 1D assumption) and the specific (temporal) discretization. In\\nour example, the computation time is decreased by a factor of 27. Our approach\\ncan offer an alternative for surrogate models, statistical relations derived\\nfrom large 3D datasets, to replace the full 3D simulations.\",\"PeriodicalId\":501270,\"journal\":{\"name\":\"arXiv - PHYS - Geophysics\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - PHYS - Geophysics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.17137\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Geophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.17137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Joining simplified physics models with coarse grids to speed-up intractable 3D time-domain simulations
Full 3D modelling of time-domain electromagnetic data requires tremendous
computational resources. Consequently, simplified physics models prevail in
geophysics, using a much faster but approximate (1D) forward model. We propose
to join the accuracy of a 1D simplified physics model with the flexibility of
coarse grids to reduce the modelling errors, thereby avoiding the full 3D
accurate simulations. We exemplify our approach on airborne time-domain
electromagnetic data, comparing the modelling error with the standard 3%
measurement noise. We find that the modelling error depends on the specific
subsurface model (electrical conductivity values, angle representing the
deviation of the 1D assumption) and the specific (temporal) discretization. In
our example, the computation time is decreased by a factor of 27. Our approach
can offer an alternative for surrogate models, statistical relations derived
from large 3D datasets, to replace the full 3D simulations.