Reservoir simulation models are used to forecast future reservoir behavior and to optimally
manage reservoir production. These models require specification of hundreds of thousands …

An efficient reservoir surveillance and monitoring technique should be able to monitor
changes in the reservoir fluid and provide a better understanding of the spatial movement …

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 …

This paper compares two ensemble-based data-assimilation methods when solving the
history-matching problem in reservoir-simulation models. The methods are the Ensemble …

A method based on the ensemble Kalman filter (EnKF) for continuous model updating with
respect to the combination of production data and 4D seismic data is presented. When the …

In applications of ensemble-based history matching, it is common to conduct Kalman gain or
covariance localization to mitigate spurious correlations and excessive variability reduction …

Time-lapse seismic data provide information on the dynamics of multiphase reservoir fluid
flow in places where no production data from wells are available. This information, in …

This paper presents a review of ensemble-based data assimilation for strongly nonlinear
problems on the characterization of heterogeneous reservoirs with different production …

This paper addresses the challenge of integrating 4D seismic data with production data in a
quantitative manner in order to improve the forecasting ability of a reservoir model and …

Distance to water front parameterization has been implemented and capability of ensemble
kalman filter to handle large number of measured data on top of the uncertain parameters …