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Titlebook: Data Assimilation; The Ensemble Kalman Geir Evensen Book 2009Latest edition Springer-Verlag Berlin Heidelberg 2009 Data assimilation.Ensem

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Lefort as Phenomenologist of the Political Optimally, it could be used for predicting the future production and to assist in the planning of new production and injection wells. A better model also provides insight and understanding regarding the properties of the reservoir.
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Introduction,en if the model is a perfect representation of reality, its solution will not describe reality unless we have perfect knowledge about the initial and boundary conditions which are often difficult to prescribe with high accuracy.
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Generalized Inverse,e formulation for the combined parameter and state estimation problem starting from Bayes’ theorem. Further, the resulting Euler–Lagrange equations are derived and we discuss some solution methods which also allow for the estimation of poorly known model parameters.
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Sampling strategies for the EnKF,y . (2002) and . (1999) for further information. It is also shown that by selecting the initial ensemble, the model noise and the measurement perturbations wisely, it is possible to achieve a significant improvement in the EnKF results, without increasing the size of the ensemble.
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An ocean prediction system,EA” integrated system, and being one of the contributors to the international Global Ocean Data Assimilation Experiment (GODAE). The system is based on the latest scientific developments in terms of ocean modelling with the Hybrid Coordinate Ocean Model (HYCOM) and data assimilation with the EnKF.
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