The ensemble Kalman filter (EnKF) and its many variants have been proven effective for data assimilation in large models, including those in atmospheric, oceanic, hydrologic, and petroleum reservoir systems. By bringing together technical experts, practitioners, researchers and students for presentations and informal interchange of information, we aim to share research results and suggest important challenges that have yet to be addressed.
Program
Download the workshop program here.
Venue
- Location: Brakanes Hotel, Ulvik
- Dates: June 20-22, 2011
Registration Fee
6,900 NOK - Includes bus transport Bergen-Ulvik roundtrip, two nights at hotel, two breakfasts, three lunches, dinner, and cultural arrangement.
Invited Speakers
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Elana Fertig
Johns Hopkins University, USA |
Indirect observations and ensemble Kalman filters: assimilating satellite observations with a local ensemble Kalman filter |
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Harrie-Jan Hendriks Franssen
Institute of Bio- and Geosciences (IBG), former ETH Zürich, Germany |
Ensemble Kalman Filter in subsurface hydrology: operational implementation and non-Gaussianity |
|
Milija Zupanski
Colorado State University, USA |
A control theory approach to nonlinearity and non-differentiability in ensemble data assimilation |
|
Geir Evensen
Statoil, Norway |
An Ensemble Smoother for Assisted History Matching |
|
Al Reynolds
University of Tulsa, USA |
Towards a More Robust Adaptation of the Ensemble Kalman Filter for Data Assimilation and Uncertainty Quantification in Reservoir Management Applications |
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Peter Jan van Leeuwen
University of Reading, UK |
Particle filters in high-dimensional geophysical systems |
