NDLI: Shrinked (1 − α) ensemble Kalman filter and α Gaussian mixture filter

Content Provider	Springer Nature Link
Author	Rezaie, Javad Eidsvik, Jo
Copyright Year	2012
Abstract	State estimation in high dimensional systems remains a challenging part of real time analysis. The ensemble Kalman filter addresses this challenge by using Gaussian approximations constructed from a number of samples. This method has been a large success in many applications. Unfortunately, for some cases, Gaussian approximations are no longer valid, and the filter does not work so well. In this paper, we use the idea of the ensemble Kalman filter together with the more theoretically valid particle filter. We outline a Gaussian mixture approach based on shrinking the predicted samples to overcome sample degeneracy, while maintaining non-Gaussian nature. A tuning parameter determines the degree of shrinkage. The computational cost is similar to the ensemble Kalman filter. We compare several filtering methods on three different cases: a target tracking model, the Lorenz 40 model, and a reservoir simulation example conditional on seismic and electromagnetic data.
Starting Page	837
Ending Page	852
Page Count	16
File Format	PDF
ISSN	14200597
Journal	Computational Geosciences
Volume Number	16
Issue Number	3
e-ISSN	15731499
Language	English
Publisher	Springer Netherlands
Publisher Date	2012-03-29
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Sequential updating Filtering EnKF Reservoir simulation Statistics Geotechnical Engineering & Applied Earth Sciences Mathematical Modeling and Industrial Mathematics Soil Science & Conservation Hydrogeology
Content Type	Text
Resource Type	Article
Subject	Computers in Earth Sciences Computational Theory and Mathematics Computer Science Applications Computational Mathematics

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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