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Volumn 2, Issue , 2009, Pages 676-693

Data assimilation coupled to evolutionary algorithms - A case example in history matching

Author keywords

[No Author keywords available]

Indexed keywords

NONLINEAR PROGRAMMING; PETROLEUM RESERVOIR ENGINEERING; PETROLEUM RESERVOIRS; STOCHASTIC SYSTEMS;

EID: 77952063906     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2118/125512-ms     Document Type: Conference Paper
Times cited : (18)

References (30)
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    • Barker, J.W.1    Cuypers, M.2    Holden, L.3
  • 9
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    • Using the Extended Kaiman Filter with a Multilayer Quasi-Geostrophic Ocean Model
    • Evensen, G., 1992. Using the Extended Kaiman Filter With a Multilayer Quasi-Geostrophic Ocean Model, J. Geophys. Res., American Geophysical Union, 97:17,905-17,924.
    • (1992) J. Geophys. Res., American Geophysical Union , vol.97 , pp. 17905-17924
    • Evensen, G.1
  • 10
    • 0028193070 scopus 로고
    • Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
    • Evensen, G., 1994, Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99:10,143-10,162
    • (1994) J. Geophys. Res. , vol.99 , pp. 10143-10162
    • Evensen, G.1
  • 11
    • 84884550570 scopus 로고    scopus 로고
    • The Ensemble Kaiman Filter: Theoretical formulation and practical implementation
    • Evensen, G.., 2003. The Ensemble Kaiman Filter: Theoretical formulation and practical implementation, Ocean Dynamics, 53:343-367.
    • (2003) Ocean Dynamics , vol.53 , pp. 343-367
    • Evensen, G.1
  • 13
    • 0008267369 scopus 로고    scopus 로고
    • Comparison of production forecast uncertainty quantification methods - An integrated study
    • Floris, F.J.T. et al., 2001. Comparison of production forecast uncertainty quantification methods - An integrated study, Petroleum Geoscience, 587.
    • (2001) Petroleum Geoscience , vol.587
    • Floris, F.J.T.1
  • 14
    • 33750502680 scopus 로고    scopus 로고
    • Estimation of high-dimensional prior and posterior covariance matrices in Kaiman filter variants
    • Furrer, R. and Bengtsson, T., 2007. Estimation of high-dimensional prior and posterior covariance matrices in Kaiman filter variants, Journal of Multivariate Analysis, 98:227-255
    • (2007) Journal of Multivariate Analysis , vol.98 , pp. 227-255
    • Furrer, R.1    Bengtsson, T.2
  • 19
    • 0032024819 scopus 로고    scopus 로고
    • Data Assimilation Using an Ensemble Kaiman Filter Technique
    • Houtekamer, P. L. and Mitchell, H. L., 1998. Data Assimilation Using an Ensemble Kaiman Filter Technique, Monthly Weather Review, 126:796-811.
    • (1998) Monthly Weather Review , vol.126 , pp. 796-811
    • Houtekamer, P.L.1    Mitchell, H.L.2
  • 20
    • 0035129828 scopus 로고    scopus 로고
    • A Sequential Ensemble Kaiman Filter for Atmospheric Data Assimilation
    • Houtekamer, P. L. and Mitchell, H. L., 2001. A Sequential Ensemble Kaiman Filter for Atmospheric Data Assimilation, Monthly Weather Review, 129:123-137.
    • (2001) Monthly Weather Review , vol.129 , pp. 123-137
    • Houtekamer, P.L.1    Mitchell, H.L.2
  • 22
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    • Efficient Implementation of the Ensemble Kalman Filter
    • University of Colorado at Denver and Health Sciences Center
    • Mandel, J., 2006. Efficient Implementation of the Ensemble Kalman Filter, UCDHSC/CCM Report No. 231, University of Colorado at Denver and Health Sciences Center.
    • (2006) UCDHSC/CCM Report No. 231
    • Mandel, J.1
  • 23
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    • A Brief Tutorial on the Ensemble Kalman Filter
    • University of Colorado at Denver and Health Sciences Center
    • Mandel, J., 2007. A Brief Tutorial on the Ensemble Kalman Filter, UCDHSC/CCM Report No. 242, University of Colorado at Denver and Health Sciences Center.
    • (2007) UCDHSC/CCM Report No. 242
    • Mandel, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.