Quantitative incorporation of 4D seismic data into reservoir history matching is an attractive proposition. The use of ensemble Kalman filter (EnKF) in this regard improves overall quality of seismic data matching and estimating reservoir parameters. We performed 4D seismic history matching of a sector model based on a North sea reservoir using real inverted 4D impedance data. Special challenges are involved when we assimilate large amount of in EnKF, and hence, a methodology based on a combination of global and local analysis scheme is used. In history matching process, we have focused on matching the acoustic impedance ratio between two time steps of several years of production. A petro-elastic modeling based on rock physics recipe of North sea reservoir is used. Uncertain reservoir parameters considered are porosity and permeability. Updated dynamic variables (pressure and water saturation) are conditioned to both production and seismic data. The large number of measurements introduced by the integration of 4D seismic data is handled by an efficient EnKF scheme with the possibility to perform localization. Global and local analysis schemes assimilate production data and seismic data respectively. In our implementation of local analysis, we used three significant regions based on flow conditions and seismic data within a given local analysis region is influenced by only variables in the same region. The posterior ensemble of models showed good match to both production data and seismic data. In most of the cases of reservoir characterization, the combined use of 4D seismic with production data improved history matching for the wells and also improved posterior impedance ratio data matching. In addition, 4D seismic data provided more information related to permeability update in the aquifer and in-fill areas. The results indicate that the proposed local analysis-based model updating scheme reduced the amount of spurious correlations and tendencies to ensemble collapse seen with global analysis.
