History matching is a type of inverse problem in which observed reservoir behavior is used
to estimate reservoir model variables that caused the behavior. Obtaining even a single …

Abstract The ensemble Kalman filter (EnKF) has become a popular method for history
matching production and seismic data in petroleum reservoir models. However, it is known …

Ensemble-based methods have gained popularity as reservoir history-matching techniques.
The advantages typically attributed to these methods include the possibility of adjusting a …

Although ensemble-based data-assimilation methods such as the ensemble Kalman filter
(EnKF) and the ensemble smoother have been extensively used for the history matching of …

Ensemble data assimilation methods have been applied with remarkable success in several
real-life history-matching problems. However, because these methods rely on Gaussian …

We present case studies on two methods for quantifying uncertainty in predictions for highly
parameterised geothermal models. One method is fully linear, while the other is nonlinear as …

Preserving plausible geological features when updating facies models is still one of the
main challenges with ensemble-based history matching. This is particularly evident for fields …

The paper focuses on a Chemical EOR study for a mature field. The field was selected due
to its volume in place and good petrophysical properties. Indeed, the preliminary screening …

One of the challenging issues of using 4D seismic data into reservoir history matching is to
compare the measured data to the model data in a consistent way. It is important to decide …

Ensemble data assimilation methods are among the most successful techniques for assisted
history matching. However, these methods suffer from sampling errors caused by the limited …