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

Indecisive

Rank issues,ber of members in the ensemble or when the matrix . for some reason has poor conditioning. In this chapter we will discuss these difficulties and propose algorithms that still makes it possible to use the EnKF analysis schemes in cases with poor conditioning. Thus, we provide an extended discussion

閑逛

發(fā)起

ADJ

Estimation in an oil reservoir simulator,d to improve the predictive capability of the models. There are economical benefits of obtaining a model which best possible represents the reservoir. 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

知識(shí)

Ibd810

嚙齒動(dòng)物

Charlatan

Statistical definitions,Basic statistical definitions which will be used in the following chapters are explained. The following is only meant to be a quick reference on statistical notation and definitions and more elaborate textbooks can be used for a comprehensive introduction to the subject.

可轉(zhuǎn)變

PSA-velocity

Model errors,We will now discuss the use of model errors in the ensemble and representer methods. A particular focus will be on the impact of time-correlated model errors. A simple scalar equation is used to illustrate the use of the ensemble and the representer methods for combined parameter and state estimation in this case.