Abstract

The placement of infill producers and injectors is an important aspect in the overall development strategy of any field and is particularly challenging for mature fields with high levels of water-cut. Previous screening approaches based upon static reservoir quality maps have limited applicability as these do not account for the drainage and swept volumes from existing wells. In contrast, direct application of formal optimization methods such as evolutionary algorithms and adjoint-based methods to high resolution geologic models may better represent reservoir dynamics but can be complex to implement or computationally prohibitive.

We propose a novel method for well placement optimization that relies on streamlines which represents the flow paths in the reservoir and the time of flight which represents the travel time of fluids along streamlines. Specifically, the streamline time of flight from the injectors provides swept volumes for injectors whereas streamline time of flight from producers gives drainage volumes for producers. These quantities can be effectively combined to a ‘total time of flight’ to locate the potential regions of unswept and undrained oil in the reservoir. Our approach utilizes a dynamic measure based on the total streamline time of flight combined with static parameters to identify potential locations for infill drilling. Areas having high value of the dynamic measure (sweet spots) are both poorly drained and poorly swept, making them attractive for drilling infill wells.

We show the power and utility of our proposed method on a mature offshore carbonate field in western India. The simulation model was history matched using a hierarchical history matching approach that follows a sequence of calibrations from global to local parameters in coarsened and fine scales. Using our proposed method on the history matched model we obtained a dynamic measure map highlighting areas suitable for drilling infill wells. Finally, we compared the performance of infill wells located using the dynamic measure map with wells located using traditional well placement techniques, for example, oil saturation map from simulation. Our proposed method consistently outperforms the traditional approaches. Subsequent field infill drilling in the field has validated our approach.

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