Conventionally, reservoir simulation is being used for studying the reservoir dynamics and identification of areas of by-passed oil. However, just as the interpretation from time-lapse is dependent on acquisition and processing conditioning, the results of the simulation study are dependent on the accuracy of the model which invariably has large scale uncertainty and ambiguity. 4D seismic, inspite of all its current limitations in carbonates, is providing another independent input in identification of bypassed oil locales. Carbonate reservoir with lower rock compressibility in general, is less sensitive to changes in fluid properties and saturation induced acoustic velocity changes. However the presence of permeability and heterogeneity within carbonate can cause significant velocity change under certain condition. A properly conditioned 4D seismic data gives a meaningful representation of the fluid dynamics and reliable estimates of saturation change.
The paper presents an integrated study of 4D seismic and reservoir simulation, carried out over one of the western offshore fields of India. Karstified Eocene carbonate is the main producer with varying degree of reservoir heterogeneity. The reservoir is developed with peripheral water injection. All the structural and property modeling features of the static model have been incorporated in a fine-grid full field simulation model. The cell dimension has been kept as 150m x 150m with 3m to 4m thickness in the main zone of interest in order to have a more representative heterogeneous model which will simulate the reservoir fluid movements more precisely. Performance history match has been carried out with over ten years of historical data. From history match the communicating and sealing nature of different faults has been inferred. Areas of good and poor horizontal and vertical communication have been identified. The simulation model was then studied with difference volume from 4D seismic. A considerably good match of two different datasets was observed which raised the confidence level in mapping bypassed oil and in placement of infill wells for brown field development. Performance prediction carried out on this model indicates that oil recovery by 2020 AD is likely to be 2 % more than that anticipated in the earlier study.