Swept Volume Calculations and Ranking of Geostatistical Reservoir Models Using Streamline Simulation

Abstract

Abstract Geostatistical techniques are increasingly being used for modeling reservoir heterogeneity and assessment of uncertainty in performance predictions. Although a large number of stochastic reservoir models or realizations may be generated, in practice only a small fraction can be considered for comprehensive flow simulations. This can be done through a ranking process. Several papers have been published in the literature on ranking of realizations. However, a consistent and generally applicable set of criteria for model ranking still remains unclear. In this paper we propose a connectivity criterion based on the streamline time-of-flight and use this criterion to rank geostatistical realizations for detailed flow simulation purposes and risk assessment. Because time-of-flights reflect fluid front propagation at various times, the connectivity in the time-of-flight provides us with a direct measure of volumetric sweep efficiency for arbitrary heterogeneity and well configuration. We show that the proposed connectivity criterion exhibits strong correlation with waterflood recovery and thus, can be used for ranking stochastic reservoir models. Unlike permeability connectivity which is a static measure independent of the flow field, the time-of-flight connectivity rigorously accounts for the interaction between the flow field and the underlying heterogeneity. Our proposed approach has been applied to synthetic as well as field examples. Synthetic examples are used to validate the sweep efficiency calculations using the streamline time-of-flight connectivity criterion by comparison with analytic solutions and published correlations. These examples also demonstrate the superiority and effectiveness of the ranking criterion over existing methods. The field example is from the North Robertson Unit, a low permeability carbonate reservoir in west Texas. Our example includes multiple patterns consisting of 27 producers and 15 injectors and illustrates the feasibility of the approach for large-scale field applications.