Qualitative well placement and drainage volume calculations based on diffusive time of flight
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abstract
Streamlines have been very effectively used for computing swept volumes and drainage volumes in oil reservoirs. However, there is an incorrect but commonly held perception that streamlines cannot be used for gas reservoirs. In fact, streamlines exist whenever there is an underlying velocity field-both in compressible and incompressible flow. In this paper we present one of the first applications of streamlines to tight gas reservoirs for drainage volume calculations of producing wells, optimal placement of infill wells.Current practice of well placement in tight gas reservoirs generally involves the use of empirical correlations based on reservoir properties and past production histories and/or pressure maps from flow simulation. No rigorous procedure is available to compute well drainage volumes in the presence of heterogeneity and hydraulic fractures, particularly for complex wells. We propose a fast approach for drainage volume calculations based on the streamlines and diffusive time of flight and demonstrate its application to optimize well placement. Our approach relies on a high frequency asymptotic solution of the diffusivity equation and emulates the propagation of a 'pressure front' in the reservoir. This allows us not only to rigorously compute the well drainage volumes as a function of time, but also to examine the potential impact of infill wells on the drainage volumes of existing producers. Using these results, we present a systematic approach to optimize well placement to maximize the estimated ultimate recoveries (EUR).We demonstrate the power and utility of our method using both synthetic and field applications. The synthetic example is used to validate our approach by establishing the consistency between the drainage volume calculations from streamlines and the EUR. The field example is from the Wamsutter gas field, one of the largest gas fields in the Rocky Mountain region. We utilize the streamline-based drainage volumes to identify depleted sands and generate a reservoir quality map to optimize future well placement based on the undepleted regions. Field application clearly demonstrates a systematic and efficient approach to optimal well placement in tight gas reservoirs. 2010.
