Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Jacob Skauvold"'
Producing geologically reasonable subsurface reservoir models which also honor wellbore and seismic data is still a major challenge for geoscientists at a range of energy and mining industries. Models based purely on geostatistics usually don’t sat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0aacf287cd0a0463987c251a5b88f7d7
https://doi.org/10.5194/egusphere-egu22-9355
https://doi.org/10.5194/egusphere-egu22-9355
Publikováno v:
Quarterly Journal of the Royal Meteorological Society
Particle filters are fully nonlinear data assimilation methods and as such are highly relevant. While the standard particle filter degenerates for high‐dimensional systems, recent developments have opened the way for new particle filters that can b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2607592747f7004b000e0c8959fd529
https://hdl.handle.net/11250/2654725
https://hdl.handle.net/11250/2654725
Autor:
Jo Eidsvik, Jacob Skauvold
Publikováno v:
Spatial Statistics
Several applications rely on data assimilation methods for complex spatio-temporal problems. The focus of this paper is on ensemble-based methods, where some approaches require estimation of covariances between state variables and observations in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a453dc1088f1061a9613cdc1d8ba1979
https://hdl.handle.net/11250/2649795
https://hdl.handle.net/11250/2649795
Publikováno v:
Geophysical Journal International. 205:796-809
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::11ce807bb78333ff1f7f7b8b04f383f5
https://doi.org/10.1093/gji/ggw029
https://doi.org/10.1093/gji/ggw029
Autor:
Jo Eidsvik, Jacob Skauvold
Publikováno v:
Basin Research
We consider the problem of conditioning a geological process-based computer simulation, which produces basin models by simulating transport and deposition of sediments, to data. Emphasising uncertainty quantification, we frame this as a Bayesian inve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49ffcb1db90737fa908e5dce93710fd5
Publikováno v:
Geophysical Research Abstracts. 2018, Vol. 20, p7930-7930. 1p.