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We discuss a two-step upscaling workflow to derive field-scale multi-phase flow parameters for depletion. The workflow was designed to increase the quality and reduce the uncertainty related to multi-phase aspects of advanced recovery methods in field-scale reservoir simulation. The upscaling workflow is applied to a realistic model, derived from an element model from the Statfjord field. In a previous paper we have demonstrated that steady-state upscaling yields valid results on the first upscaling step. In this paper, main focus is put on the second step, the transition from a fine-gridded geological model to a coarse-gridded simulation model. We show that in this case our steady-state upscaling tools are presently not able to accurately capture the effects of gravity. A dynamic upscaling (history match) was performed too, and gave a slightly better match. At present, the workflow has a relatively slow turnaround time, but this might be significantly improved by further development and automation of the different methods and tools that are involved. In essence, the upscaling workflow still needs to be improved. Introduction Extending the lifetime and increasing oil recovery of a reservoir requires reliable reservoir simulation models that allow the accurate prediction of production profiles for different IOR strategies. Major ingredients to these simulation models are multi-phase flow parameters, such as relative permeability and capillary pressure, properly adapted to the relevant flow phenomena and the spatial resolution of the simulation model. Traditionally, relatively little work is spent on preparing multi-phase flow parameters for a reservoir simulation model, as far as the adaptation to the relevant flow phenomenon and the resolution of the model is concerned. Usually, SCAL results are compiled and applied either directly or slightly corrected. At best, a so-called ‘dynamic upscaling’ (history match of a simulation model with respect to relative permeability and capillary pressure) is performed. This approach limits, however, the predictive capability of the simulation models in that it requires historic field data. Such an approach is useful after for example a water injection pilot, when the experiences from the pilot project are to be included into the full field simulation model. If, however, a completely new drainage strategy is to be applied, historic data may be of very limited value. However, given modern tools for single-phase and multi-phase upscaling, a two-stage workflow has been developed, that eventually might provide a rigorous solution to this problem [1,2,3]. Major ingredients to this upscaling technique are i) appropriate rock models that provide process dependent pore-scale flow parameter through advanced network modelling, ii) detailed lithofacies models for all relevant flow units, and iii) a sound geological model. The pore-scale flow parameters (rock curves) are then upscaled to facies-scale through steady-state methods, thereby accounting for small-scale heterogeneities as well as effects of capillarity and buoyancy. This process results in a set of flow parameter for each flow unit in the geological model. Upscaling from the geological model to the simulation model finally yields appropriate field-scale flow parameters. A sketch of this workflow is shown in Figure 1.

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The paper presents the results of an integrated full field reservoir description study that has been carried out on the Statfjord reservoir in the Statfjord field. Two major issues addressed are reservoir modeling and history matching of the simulation model. Geostatistical modeling was used as a main tool to integrate all available quantitative and qualitative data into a high resolution geological model of the reservoir. Stratigraphic framework for the modeling was set up by the high resolution sequence stratigraphic interpretation in 34 development and 11 exploration wells. Based on this interpretation, the new reservoir zonation was established and major facies types were identified. The reservoir modeling created a solid base for building a reservoir simulation model. Advanced grid builder allowed for accurate representation of such important features as heavily slanted faults and typical heterogeneity pattern. Nonlinear regression based technique was consistently applied to match reservoir performance data for 16 years of production. Introduction Statfjord field, discovered in 1974, is one of the largest oil fields in the North Sea, with an original oil in place of over a billion Sm3 and estimated recovery factor exceeding 60%. The field is located in the prolific northern part of the Viking graben on the U.K./Norway boundary. The Statfjord field which is 24 km long and averages 4 km in width is located in a fault-block structure which is tilted at about 70 to the west (Fig. 1). On the east, the field is bounded by a major boundary fault system. Between the structural crest and the boundary fault, the reservoirs are cut by rotational faulting and truncated by erosion events. The two most important reservoir intervals are the Middle Jurassic Brent Group and the Upper Triassic to Lower Jurassic Statfjord Formation. The Statfjord reservoir which is the focus of this paper, contains around 20% of the total original oil in place. The Brent reservoir is developed under line water drive, whereas the Statfjord reservoir is under high-pressure miscible gas flood. The development scheme utilizes 3 gravity-based Condeep platforms - A, B, and C which became operational in 1979, 1982, and 1985 respectively. Continuous gas flood led to an effect that the upflank area covered by the first line of the oil producers became gas flooded and a "wedge zone" was formed. The wedge zone, located between initial drainage line and OWC, contains the bulk of the oil to be produced. At this stage, the primary oil producers were either sidetracked or converted to the Brent reservoir. The two first horizontal oil producers targeting the wedge zone, were drilled in 1990. This marked a change of the management strategy towards production from the wedge zone (Figs. 1 and 2). The current status of the reservoir is shown in Tables 1 and 2. With production from Upper Statfjord declining rapidly, the Raude formation will play a more important role in efforts to sustain the total production from the reservoir. The next phase in the development of the Statfjord reservoir will most likely be updip water injection in Upper Statfjord and downdip WAG injection in Lower Statfjord. An existing full-field reservoir simulation model that has been adequate for reservoir management purposes in the plateau production period is no longer capable to deliver sound and reliable basis for crucial management decisions. To meet the new challenges a Statfjord field reservoir description project was initiated in 1993. The main goal of the project was to generate an improved reservoir description by developing new technologies in a multidisciplinary environment in order to:–Better optimize and predict future production.–Identify remaining reserves.–Optimize well placement and productivity. P. 915^