Open Access
Issue
Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles
Volume 67, Number 5, September-October 2012
Page(s) 841 - 855
DOI https://doi.org/10.2516/ogst/2012044
Published online 14 November 2012
  • Evensen G. (1994) Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res. 99, C5, 10, 143, 162.
  • Lorentzen R.J., Kåre Fjelde K., Frøyen J., Lage A.C.V.M., Nævdal G., Vefring E.H. (2001) Underbalanced and low-head drilling operations : Real time interpretation of measured data and operational support, SPE Annual Technical Conference and Exhibition, 30 September-3 October, SPE Paper 71384.
  • Nævdal G., Mannseth T., Vefring E.H. (2002) Near-well reservoir monitoring through ensemble Kalman filter, SPE/DOE Improved Oil Recovery Symposium, Tulsa, Oklahoma, 13-17 April, SPE Paper 75235.
  • Haugen V., Natvik L.J., Evensen G., Berg A., Flornes K., Nævdal. G. (2006) History matching using the ensemble Kalman filter on a North Sea field case, SPE Annual Technical Conference and Exhibition, San Antonio, Texas, 24-27 Sept. Society of Petroleum Engineers, SPE Paper 102430.
  • Evensen G., Hove J., Meisingset H.C., Reiso E., Seim K.S., Espelid Ø. (2007) Using the EnKF for assisted history matching of a North Sea reservoir model, SPE Reservoir Simulation Symposium, Woodlands, Texas, 26-28 February, Society of Petroleum Engineers, SPE Paper 106184.
  • Bianco A., Cominelli A., Dovera L., Naevdal G., Vallès B. (2007) History matching and production forecast uncertainty by means of the ensemble Kalman filter : A real field application, SPE Europec/EAGE Annual Conference and Exhibition, London, UK, 11-14 June, Society of Petroleum Engineers, SPE Paper 107161.
  • Aanonsen S.I., Naevdal G., Oliver D.S., Reynolds A.C., Vallès B. (2009) The ensemble Kalman filter in reservoir engineering – a review, SPE J. 14, 3, 393-412.
  • Seiler A., Aanonsen S.I., Evensen G., Rivenæs J.C. (2010) Structural surface uncertainty modeling and updating using the ensemble Kalman filter, SPE J. 15, 4, 1062-1076.
  • Chen Y., Oliver D.S. (2012) Localization of ensemble-based control-setting updates for production optimization, SPE J. 17, 1, 122-136.
  • Lorentzen R.J., Flornes K.M., Nævdal G. (2012) History matching channelized reservoirs using the ensemble Kalman filter, SPE J. 17, 1, 137-151.
  • Verlaan M., Heemink A.W. (2001) Nonlinearity in data assimilation applications : A practical method for analysis, Mon. Weather Rev. 129, 6, 1578-1589. [CrossRef]
  • Bishop C.H., Etherton B.J., Majumdar S.J. (2001) Adaptive sampling with the ensemble transform Kalman filter. Part I : Theoretical aspects, Mont. Weather Rev. 129, 420-436. [CrossRef]
  • Tippett M.K., Anderson J.L., Bishop C.H., Hamill T.M., Whitaker J.S. (2003) Ensemble square-root filters, Mon. Weather Rev. 131, 7, 1485-1490. [CrossRef]
  • Vallès B., Nævdal G. (2009) Revisiting Brugge case study using a hierarchical ensemble Kalman filter, International Petroleum Technology Conference, Doha, Qatar, 7-9 Dec., IPTC-14074.
  • Anderson J.L. (2007) Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter, Physica D 230, 99-111. [CrossRef] [PubMed]
  • Stordal A.S., Karlsen H.A., Nævdal G., Skaug H.J., Vallès B. (2011) Bridging the ensemble Kalman filter and particle filters : the adaptive Gaussian mixture filter, Comput. Geosci. 15, 2, 293-305. [CrossRef] [PubMed]
  • Burgers G., van Leeuwen P.J., Evensen G. (1998) On the analysis scheme in the ensemble Kalman filter, Mon. Weather Rev. 126, 1719-1724. [CrossRef]
  • Houtekamer P.L., Mitchell L.H. (1998) Data assimilation using an ensemble Kalman filter technique, Mon. Weather Rev. 126, 796-811. [CrossRef]
  • Whitaker J.S., Hamil T.M. (2002) Ensemble data assimilation without perturbed observations, Mon. Weather Rev. 130, 1913-1924. [CrossRef]
  • Sakov P., Oke P.R. (2008) Implications of the form of the ensemble transformation in the ensemble square root filters, Mon. Weather. Rev. 136, 1042-1053. [CrossRef]
  • Julier S.J., Uhlmann J.K. (1997) A new extension to the Kalman filter to nonlinear systems, Proceedings of AeroSens : The 11th International Symposium on Aerospace/Defense Sensing, Simulation and Controls, Orlando, Florida, 20-25 Avril.
  • Floris F.J.T., Bush M.D., Cuypers M., Roggero F., Syversveen A.R. (2001) Methods for quantifying the uncertainty of production forecasts : a comparative study, Petrol. Geosci. 7, 87-96. [CrossRef]
  • PUNQ-S3 (2012) website : http://www3.imperial.ac.uk/earthscienceandengineering/research/perm/punq-s3model.
  • Deutsch C.V., Journel A.G. (1998) GSLIB Geostatistical Software Library and User’s Guide, Applied Geostatistics Series, Oxford University Press, second edition.
  • Lorentzen R.J., Nævdal G., Vallès B., Berg A.M., Grimstad A.-A. (2005) Analysis of the ensemble Kalman filter for estimation of permeability and porosity in reservoir models, SPE Annual Technical Conference and Exhibition, Dallas, Texas, 9-12 October, SPE Paper 96375.

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.