Reservoir managers would like to know the current state of their field and be able to see into the future to know how it will change. The former requires information about current fluid sweep and pressure change while the latter requires accurate reservoir description and a predictive tool such as a simulation model. Important decisions can then be made regarding facility maintenance and well optimization, but more importantly, unswept areas can be identified and new wells drilled. Conventionally, simulation models have been used to determine the possible reservoir state and predict its behaviour. The modelling commonly begins with the geologist who creates a number of static geomodels, often constrained to the core data and the petrophysicist’s well log data in addition to the geophysicist’s pre-production 2D or 3D seismic. The upscaled models are then modified by an engineer so that they match static and dynamic well data, including fluid production rates and local pressures. Because the wells are widely spaced, many possible solutions exist where the well data will match. Time-lapse (4D) seismic can reduce the non-uniqueness by identifying changes in fluid saturation and/or pressures. This information is now available in qualitative form almost routinely in a number of North Sea and Gulf of Mexico fields, but the goal is to integrate this data quantitatively with the modelling process together with other available data. To achieve this goal, we have developed an automated history matching method to include as much reservoir data as is necessary and sufficient, including core and well logs, seismic, production data, SCAL, etc. Here, we apply our method to the Schiehallion UKCS reservoir where we update the operator’s model using geostatistical approaches and obtain an improved match to seismic and a good match to production data. Finally, the uncertainty of the parameters and predicted behaviour is analysed.