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Volumn 2, Issue , 2009, Pages 750-766

Estimation of depths of fluid contacts by history matching using iterative ensemble kalman smoothers

Author keywords

[No Author keywords available]

Indexed keywords

ITERATIVE METHODS; UNCERTAINTY ANALYSIS;

EID: 70449633012     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2118/119056-ms     Document Type: Conference Paper
Times cited : (9)

References (23)
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    • Bianco, A., A. Cominelli, L. Dovera, G. Návdal, and B. Vallès, History matching and production forecast uncertainty by means of the ensemble Kalman filter: A real field application (SPE-107161), in EAGE/EUROPEC Conference and Exhibition, London, U.K., 2007.
    • (2007) EAGE/EUROPEC Conference and Exhibition
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  • 3
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    • A strategy for operational implementation of 4D-Var using an incremental approach
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    • Courtier, P.1    Thépaut, J.-N.2    Hollingsworth, A.3
  • 4
    • 34249027618 scopus 로고    scopus 로고
    • Efficient and robust reservoir model updating using ensemble Kalman filter with sensitivity-based covariance localization (SPE-106144)
    • Devegowda, D., E. Arroyo-Negrete, A. Datta-Gupta, and S. G. Douma, Efficient and robust reservoir model updating using ensemble Kalman filter with sensitivity-based covariance localization (SPE-106144), in SPE Reservoir Simulation Symposium, 2007.
    • (2007) SPE Reservoir Simulation Symposium
    • Devegowda, D.1    Arroyo-Negrete, E.2    Datta-Gupta, A.3    Douma, S.G.4
  • 5
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    • Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
    • 99, 10
    • Evensen, G., Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, Journal of Geophysical Research, 99, 10, 143-10, 162, 1994.
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    • Evensen, G.1
  • 8
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    • Methods for quantifying the uncertainty of production forecasts: A comparative study
    • SUPP
    • Floris, F. J. T., M. D. Bush, M. Cuypers, F. Roggero, and A.-R. Syversveen, Methods for quantifying the uncertainty of production forecasts: A comparative study, Petroleum Geoscience, 7(SUPP), 87-96, 2001.
    • (2001) Petroleum Geoscience , vol.7 , pp. 87-96
    • Floris, F.J.T.1    Bush, M.D.2    Cuypers, M.3    Roggero, F.4    Syversveen, A.-R.5
  • 9
    • 38349192524 scopus 로고    scopus 로고
    • An iterative ensemble Kalman filter for multiphase fluid flow data assimilation
    • Gu, Y. and D. S. Oliver, An iterative ensemble Kalman filter for multiphase fluid flow data assimilation, SPE Journal, 12(4), 438-446, 2007.
    • (2007) SPE Journal , vol.12 , Issue.4 , pp. 438-446
    • Gu, Y.1    Oliver, D.S.2
  • 11
    • 0035129828 scopus 로고    scopus 로고
    • A sequential ensemble Kalman filter for atmospheric data assimilation
    • Houtekamer, P. L. and H. L. Mitchell, A sequential ensemble Kalman filter for atmospheric data assimilation, Monthly Weather Review, 129(1), 123-137, 2001.
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    • Houtekamer, P.L.1    Mitchell, H.L.2
  • 19
    • 33846187189 scopus 로고    scopus 로고
    • Real-time reservoir model updating using ensemble Kalman filter with confirming option
    • Wen, X.-H. and W. H. Chen, Real-time reservoir model updating using ensemble Kalman filter with confirming option, SPE Journal, 11(4), 431-442, 2006.
    • (2006) SPE Journal , vol.11 , Issue.4 , pp. 431-442
    • Wen, X.-H.1    Chen, W.H.2
  • 20
    • 34447293103 scopus 로고    scopus 로고
    • Some practical issues on real-time reservoir model updating using ensemble Kalman filter
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    • Wen, X.-H.1    Chen, W.H.2
  • 21
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    • Assessing the uncertainty in reservoir description and performance predictions with the ensemble Kalman filter
    • SPE 95750-PA
    • Zafari, M. and A. C. Reynolds, Assessing the uncertainty in reservoir description and performance predictions with the ensemble Kalman filter, SPE Journal, 12(3), 382-391, 2007, SPE 95750-PA.
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    • Zafari, M.1    Reynolds, A.C.2
  • 22
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    • Tulsa, 20-23 April
    • Zhao, Y., A. C. Reynolds, and G. Li, Generating facies maps by assimilating production data and seismic data with the ensemble Kalman filter (SPE-113990), in Proceedings of the 2008 SPE Improved Oil Recovery Symposium, Tulsa, 20-23 April, 2008.
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    • Zhao, Y.1    Reynolds, A.C.2    Li, G.3
  • 23
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