Geir Evensen

Job Position: 
Adjunct position
Research Group: 
E-mail: 

Research interests

Development and applications of ensemble-based data assimilation methods.

Personal Home Page: 
EnKF page

Project leader of the following projects

  1. EmblA: Ensemble-based data assimilation for environmental monitoring and prediction
  2. eVITA-EnKF: Forecasting non-linear systems using the ensemble Kalman filter and related methods

Peer Review Publications and Books

53 total publications.

2021

  1. Evensen G. Formulating the history matching problem with consistent error statistics. Computational Geosciences. 2021;

2020

  1. Soares R, Luo X, Evensen G, Bhakta T. 4D seismic history matching: Assessing the use of a dictionary learning based sparse representation method. Journal of Petroleum Science and Engineering. 2020;195.
  2. Evensen G, Amezcua J, Bocquet M, Carrassi A, Farchi A, Fowler A, et al. An international initiative of predicting the SARS-CoV-2 pandemic using ensemble data assimilation. Foundations of Data Science (FoDS). 2020;

2019

  1. Soares RV, Luo X, Evensen G. Sparse Representation of 4D Seismic Signal Based on Dictionary Learning. In: SPE Norway One Day. 2019.
  2. Evensen G. Accounting for model errors in iterative ensemble smoothers. Computational Geosciences. 2019;23(4).
  3. Raanes PN, Stordal AS, Evensen G. Revising the stochastic iterative ensemble smoother. Nonlinear processes in geophysics. 2019;26(3).
  4. Evensen G, Raanes PN, Stordal AS, Hove J. Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching. Frontiers in Applied Mathematics and Statistics. 2019;5(47).

2018

  1. Evensen G. Analysis of iterative ensemble smoothers for solving inverse problems. Computational Geosciences. 2018;22(3).
  2. Evensen G, Eikrem KS. Conditioning reservoir models on rate data using ensemble smoothers. Computational Geosciences. 2018;22(5).
  3. Carrassi A, Bocquet M, Bertino L, Evensen G. Data assimilation in the geosciences - An overview of methods, issues and perspectives. WIREs Climate Change. 2018;
  4. Luo X, Lorentzen RJ, Valestrand R, Evensen G. Correlation-Based Adaptive Localization for Ensemble-Based History Matching: Applied To the Norne Field Case Study. SPE Reservoir Evaluation and Engineering. 2018;
  5. Evensen G. Introducing Stochastic Model Errors In Ensemble-Based History Matching. In: ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery, 3–6 September 2018, Barcelona, Spain. 2018.
  6. Luo X, Lorentzen RJ, Valestrand R, Evensen G. Correlation-Based Adaptive Localization for Ensemble-Based History Matching: Applied to the Norne Field Case Study. In: SPE Norway One Day Seminar 2018. 2018.

2017

  1. Evensen G. Analysis of iterative ensemble smoothers for solving inverse problems. Computational Geosciences. 2017;

2010

  1. Seiler A. Reservoir structural model updating using the Ensemble Kalman Filter. 2010.
  2. Sakov P, Evensen G, Bertino L. Asynchronous data assimilation with the EnKF. Tellus A [Internet]. 2010;62A. Available from: http://onlinelibrary.wiley.com/doi/10.1111/j.1600-0870.2009.00417.x/abstract
  3. Seiler A, Aanonsen SI, Evensen G, Rivenæs JC. Structural Surface Uncertainty Modeling and Updating Using the Ensemble Kalman Filter. SPE Journal [Internet]. 2010;15. Available from: http://dx.doi.org/10.2118/125352-PA

2009

  1. Seiler A, Evensen G, Skjervheim J-A, Hove J, Vabø JG. Using the EnKF for history matching and uncertainty quantification of complex reservoir models. In: Biegler L, Biros G, Ghattas O, Heinkenschloss M, Keyes D, Mallick B, et al. Computational Methods for Large-Scale Inverse Problems and Quantification of Uncertainty. 2009.
  2. Evensen G. Data Assimilation: The Ensemble Kalman Filter [Internet]. 2nd editionnd ed. 2009. Available from: http://www.amazon.com/Data-Assimilation-Ensemble-Kalman-Filter/dp/3642037100/ref=reader_auth_dp
  3. Evensen G. The ensemble Kalman filter for combined state and parameter estimation. Control systems magazine [Internet]. 2009;29:83-104. Available from: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4939313

Other Publications

2011

  1. Bertino L, Evensen G, Sakov P, Counillon F, Simon E, Bojarova J, et al. Forecasting non-linear systems with the Ensemble Kalman Filter and related data assimilation methods (eVITA-EnKF). 2011.

2010

  1. Seiler A. Reservoir structural model updating using the Ensemble Kalman Filter. 2010.

2009

  1. Evensen G. Data Assimilation: The Ensemble Kalman Filter [Internet]. 2nd editionnd ed. 2009. Available from: http://www.amazon.com/Data-Assimilation-Ensemble-Kalman-Filter/dp/3642037100/ref=reader_auth_dp
  2. Seiler A, Rivenæs JC, Aanonsen SI, Evensen G. Structural Uncertainty modelling and updating by production data integration. 2009 SPE/EAGE Reservoir Characterization and Simulation Conference. 2009;
  3. Seiler A, Evensen G, Skjervheim J-A, Hove J, Vabø JG. Using the EnKF for history matching and uncertainty quantification of complex reservoir models. In: Biegler L, Biros G, Ghattas O, Heinkenschloss M, Keyes D, Mallick B, et al. Computational Methods for Large-Scale Inverse Problems and Quantification of Uncertainty. 2009.
  4. Seiler A, Evensen G, Skjervheim J-A, Hove J, Vabø JG. Advanced reservoir management workflow using an EnKF based assisted history matching method. The 2009 SPE Reservoir Simulation Symposium, 65533. 2009;

2008

  1. Counillon F. Ensemble-based data assimilation with an eddy-resolving model of the Gulf of Mexico. 2008.

2007

  1. Evensen G, Hove J, Meisingset HC, Reiso E, Seim KS, Espelid Ø. Using the EnKF for Assisted History Matching of a North Sea Reservoir Model. SPE 106184. SPE Reservoir Simulation Symposium. 2007;:13.
  2. Lisæter KA. A coupled ice - ocean data assimilation system for Arctic monitoring and prediction. 2007.

2006

  1. Johannessen J, Pettersson LH, Eldevik T, Durand D, Evensen G, Winther N, et al. Coastal Physical and Biochemical Processes [Internet]. In: Remote Sensing of the Marine Environment. 2006. p. 360. P. 179-196.Available from: https://eserv.asprs.org/eseries/staticcontent/staticpages/4578.html
  2. Evensen G. Data Assimilation -The Ensemble Kalman Filter. 2006.
  3. Haugen V, Natvik L-J, Evensen G, Berg A, Flornes K, Nævdal G. History matching using the ensemble Kalman filter on a North Sea field case. SPE 102430 [Internet]. 2006;Available from: http://www.spe.org

2005

  1. Skjervheim J-A, Evensen G, Aanonsen SI, Ruud BO, Johansen TA. Incorporating 4D seismic data in reservoir simulation models using ensemble Kalman filter. SPE 95789 [Internet]. 2005;Available from: http://www.spe.org

2004

  1. Albretsen J, Winther N, Søiland H, Røed LP, Brusdal KK, Engedahl H, et al. Models in MONCOZE. 2004.

2003

  1. Jacob AA, Hamre T, Evensen G, Mughal KA. Developing a Marine Information System by Integrating Existing Ocean Models Using Object-Oriented Technology. Marine Geodesy. 2003;26:87-106.
  2. Natvik L-J, Evensen G. Assimilation of ocean colour data into a biochemical model of the North Atlantic. Part 2. Statistical analysis. journal of Marine Systems. 2003;:155-169.
  3. Lisæter KA, Rosanova JJ, Evensen G. Assimilation of ice concentration into a coupled ice ocean model using the Ensemble Kalman Filter. 2003.
  4. Bertino L, Evensen G. The DIADEM/TOPAZ monitoring and prediction system for the North Atlantic. 3rd EuroGOOS conference: Building the European capacity in Operational Oceanography, Athens, Greece 3-6 Dec 2002. Elsevier Oceanography Series. 2003;
  5. Evensen G, Gaspar P, Johannessen J, Lefevre F, Sagen H, Stephens R, et al. Envisat monitoring and forecasting services for offshore industry, EMOFOR. 2003.
  6. Natvik L-J, Evensen G. Assimilation of ocean colour data into a biochemical model of the North Atlantic. Part 1. Data assimilation experiments. Journal of Marine Systems. 2003;:127-153.
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