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Two-point or multiple-point statistics? A comparison between the ensemble Kalman filtering and the ensemble pattern matching inverse methods

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Two-point or multiple-point statistics? A comparison between the ensemble Kalman filtering and the ensemble pattern matching inverse methods

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Li, L.; Srinivasan, S.; Zhou, H.; Gomez-Hernandez, JJ. (2015). Two-point or multiple-point statistics? A comparison between the ensemble Kalman filtering and the ensemble pattern matching inverse methods. Advances in Water Resources. 86:297-310. doi:10.1016/j.advwatres.2015.05.014

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/73816

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Title: Two-point or multiple-point statistics? A comparison between the ensemble Kalman filtering and the ensemble pattern matching inverse methods
Author:
UPV Unit: Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos - Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports
Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
Issued date:
Abstract:
The Ensemble Kalman Filter (EnKF) has been commonly used to assimilate real time dynamic data into geologic models over the past decade. Despite its various advantages such as computational efficiency and its capability ...[+]
Subjects: Multiple-point statistics , Rejection sampling , Conditional simulation , Ensemble Kalman filter , Inverse method
Copyrigths: Reserva de todos los derechos
Source:
Advances in Water Resources. (issn: 0309-1708 )
DOI: 10.1016/j.advwatres.2015.05.014
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.advwatres.2015.05.014
Thanks:
The first three authors gratefully acknowledge the financial support by the U.S. Department of Energy through project DE-FE0004962. The fourth author acknowledges the financial support by the Spanish Ministry of Economy ...[+]
Type: Artículo

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