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, 2016
Registration Fee
9,950 NOK - Includes bus transport Bergen-Ulvik roundtrip, conference, three lunches, two dinners, two nights at hotel, and guided tour at Lekve Farm.
Invited Speakers
|
Arnold Heemink
TU Delft, Netherlands |
Ensemble methods for variational data assimilation |
|
Alexander Barth
University of Liège, Belgium |
Local ensemble assimilation scheme with global constraints and conservation |
|
Raul Tempone
KAUST, Saudi Arabia |
A short overview of Multilevel Monte Carlo methods with applications in Ensemble Kalman Filtering |
|
Marc Bocquet
Université Paris-Est, France |
On the convergence of (ensemble) Kalman filters and smoothers onto the unstable subspace |
Presentations
| Jesper Sandvig Mariegaard | talk | Assimilation of along-track altimetry data with correlated measurement errors in MIKE 21/3 FM |
| Abhishek Shah | talk | An efficient ensemble data assimilation approach to deal with range limited observations |
| Jostein Blyverket | talk | Understanding soil moisture in the northern areas: Toward an integrated representation of the arctic hydrological cycle |
| Marc Bocquet | talk | On the convergence of (ensemble) Kalman filters and smoothers onto the unstable subspace |
| Patrick Raanes | talk | On the ensemble Rauch-Tung-Striebel smoother and its equivalence to the ensemble Kalman smoother |
| Geir Evensen | talk | Stable and fast inversion with large data sets and non-diagonal R |
| Claudia Schillings | talk | Analysis of the Ensemble Kalman Filter for Inverse Problems |
| Håkon Hoel | talk | Multilevel Monte Carlo Ensemble Kalman filtering (MLEnKF) in finite and infinite dimensions |
| Alexander Litvinenko | talk | Approximation of non-linear Bayesian Update |
| Jan Magnusson | talk | Improving physically based snow simulations by assimilating snow depths using the particle filter |
| Bogdan Sebacher | talk | Different parameterizations of the initial ensemble for a channelized reservoir in an assisted history matching context |
| Hans Wackernagel | talk | Geostatistical change-of-support models for irregular grids |
| Geir Nævdal | talk | Ensemble based data assimilation for a multi-compartment porous media model |
| Xiaodong Luo | talk | Efficient big data assimilation through sparse representation: A case study in 4D seismic history matching |
| Patrick Raanes | talk | On the ensemble Rauch-Tung-Striebel smoother and its equivalence to the ensemble Kalman smoother |
Additional presentations may be available by contacting the presenters.
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