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Efficient geostatistical inversion of transient groundwater flow using preconditioned nonlinear conjugate gradients

We present a preconditioned conjugate gradient method for geostatistical inversion. The prior covariance matrix is used as preconditioner at negative computational cost. The approach incorporates linearized uncertainty quantification. The method is particularly efficient for the inversion of transie...

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Hauptverfasser: Klein, Ole (VerfasserIn) , Cirpka, Olaf A. (VerfasserIn) , Bastian, Peter (VerfasserIn) , Ippisch, Olaf (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: April 2017
In: Advances in water resources
Year: 2017, Jahrgang: 102, Pages: 161-177
ISSN:1872-9657
DOI:10.1016/j.advwatres.2016.12.006
Online-Zugang:Verlag, Volltext: http://dx.doi.org/10.1016/j.advwatres.2016.12.006
Volltext
Verfasserangaben:Ole Klein, Olaf A. Cirpka, Peter Bastian, Olaf Ippisch
Beschreibung
Zusammenfassung:We present a preconditioned conjugate gradient method for geostatistical inversion. The prior covariance matrix is used as preconditioner at negative computational cost. The approach incorporates linearized uncertainty quantification. The method is particularly efficient for the inversion of transient data. Transient inversion may speed up experiments and improve quality of inversion results.
Beschreibung:Gesehen am 16.11.2017
Beschreibung:Online Resource
ISSN:1872-9657
DOI:10.1016/j.advwatres.2016.12.006

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