A distance-based representation of reservoir uncertainty: The metric EnKF

ECMOR 2008 - 11th European Conference on the Mathematics of Oil Recovery

Volumn , Issue , 2008, Pages

  Caers, J ^a   Park, K ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; COVARIANCE MATRIX; EIGENVALUES AND EIGENFUNCTIONS; GAUSSIAN DISTRIBUTION; INTELLIGENT SYSTEMS; MONTE CARLO METHODS; RADIAL BASIS FUNCTION NETWORKS; UNCERTAINTY ANALYSIS;

EIGENVALUE DECOMPOSITION; HIGH DIMENSIONAL SPACES; HIGH-RESOLUTION MODELS; KARHUNEN LOEVE EXPANSION; POSTERIOR DISTRIBUTIONS; RADIAL BASIS FUNCTIONS; TRADITIONAL APPROACHES; UNCERTAINTY QUANTIFICATIONS;

RESERVOIR MANAGEMENT;

EID: 85087188723     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3997/2214-4609.20146404     Document Type: Conference Paper

References (13)

1. Borg, I., and Groenen, P., 1997, Modern multidimensional scaling: theory and applications: Springer, New-York, 614p
2. th International Geostatistics Conference, Santiago Chile, Dec 1-5, 2008.
3. Cox, T. F. and Cox, M. A. A., 1994, Multidimensional scaling. London: Chapman and Hall.
4. Evensen, G.: The Ensemble Kalman Filter: Theoretical Formulation and Practical Implementation, Ocean Dynamics (2003) 53, 3431
5. Houtekamer, P.L. and Mitchell, H.L.: Data Assimilation Using an Ensemble Kalman Filter Technique, Monthly Weather Review (1998) 126, 796.
6. Kalman, R.E.: A New Approach to Linear Filtering and Prediction Problems, J. of Basic Engineering (1960) 82, 35.
7. th International Geostatistics Conference, Santiago Chile, Dec 1-5, 2008.
8. Sarma, P., 2006, Efficient Closed-Loop Optimal Control of Petroleum Reservoirs Under Uncertainty: PhD Dissertation, Stanford University, USA, 201 p.
9. Scheidt, C. and Caers, J., 2008a, Representing Spatial Uncertainty Using Distances and Kernels, Mathematical Geosciences, Accepted for publication.
10. th International Geostatistics Conference, Santiago Chile, Dec 1-5, 2008.
11. Scheidt, C., and Caers, J., 2008c, A New Method for Uncertainty Quantification Using Distances and Kernel Methods - Application to a Deepwater Turbidite Reservoir, submitted to SPE Journal.
12. Schöelkopf, B., Smola, A., 2002, Learning with Kernels: MIT Press, Cambridge, MA, 626 p.
13. Shawe-Taylor, J., Cristianni, N., 2004, Kernel Methods for Pattern Analysis: Cambridge University Press, 462 p.