Quantifying Monte Carlo uncertainty in ensemble Kaiman filter

dc.contributor.author	Thulin, Kristian
dc.contributor.author	Nævdal, Geir
dc.date.accessioned	2019-12-12T06:38:51Z
dc.date.available	2019-12-12T06:38:51Z
dc.date.issued	2009
dc.identifier.uri	http://hdl.handle.net/11250/2632833
dc.description.abstract	The ensemble Kaiman filter (EnKF) is currently considered one of the most promising methods for conditioning reservoir simulation models to production data. The EnKF is a sequential Monte Carlo method based on a low rank approximation of the system covariance matrix.	nb_NO
dc.description.sponsorship	Research Council of Norway	nb_NO
dc.language.iso	eng	nb_NO
dc.publisher	IRIS Miljø	nb_NO
dc.title	Quantifying Monte Carlo uncertainty in ensemble Kaiman filter	nb_NO
dc.type	Research report	nb_NO
dc.source.issue	Report IRIS - 2009/001	nb_NO
dc.source.pagenumber	16	nb_NO
dc.subject.nsi	Naturvitenskap	nb_NO