the ensemble Kalman filter has become established as a viable and popular method for data assimilation in very large models including those describing atmospheric, oceanic, and petroleum reservoirs systems. Although the basic concept is straightforward, successful practical implementation has often required modifications that are problem specific. Methods that are highly successful in meteorology have not always been appropriate for porous media flow. By bringing together experts from diverse fi

Program

Download the workshop program here.

Venue

  • Location: First Hotel Marin
  • Dates: June 22-24, 2009

Registration Fee

6,250 NOK - Includes two nights at hotel, two breakfasts, three lunches, two dinners, and cultural arrangement.

Invited Speakers

Yan Chen
Chevron, 		The Brugge field model as a test case for data assimilation
Akhil Datta-Gupta
Texas A&M University, 		A hybrid ensemble Kalman filter with coarse scale constraints
Geir Evensen
StatoilHydro & Nansen center, 		A discussion on the EnKF analysis scheme
Dennis McLaughlin
Massachusetts Institute of Technology, 		Progress on feature-based ensemble data assimilation methods
Henning Omre
Norwegian University of Science and Technology, 		Ideas on a skewed ensemble Kalman filter
Al Reynolds
University of Tulsa, 		Failings and fixes of EnKF for nonlinear dynamics with non-Gaussian priors
Pavel Sakov
Nansen center, 		Ensemble Square Root Filters
Hans Wackernagel
Mines-ParisTech, 		Detecting and quantifying epidemics by particle filtering