Current practice of well placement in tight gas reservoirs generally involves the use of empirical correlations based on reservoir properties and analysis of past production and pressure histories and/or pressure maps from flow simulation. No rigorous procedure is available to compute well drainage volumes in the presence of permeability heterogeneity controlled by the distribution and orientation of natural fractures. The situation is complicated by the routine use of horizontal and complex wells in tight gas reservoirs and the presence of multistage hydraulic fractures. The computation of drainage volume will be critical to our understanding of the interaction between existing wells, potential infill locations and the estimated ultimate recovery (EUR) computations for infill wells.

We propose a rigorous approach for well drainage volume calculations in tight gas reservoirs based on the flux field derived from dual porosity finite-difference simulation 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 along gas streamlines. The proposed approach is a generalization of the radius of drainage concept in well test analysis (Lee, 1982). The method allows us not only to compute rigorously the well drainage volumes as a function of time but also 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 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 consistency between the drainage volume calculations from streamlines and the EUR computations based on detailed finite-difference simulations. We also present comparison of our approach with analytic drainage volume calculations for simplified cases. The field example is from one of the tight gas fields in the Rocky Mountain region. We utilize the streamline-based drainage volumes to identify depleted sands and generate a reservoir ‘depletion capacity’ map to optimize infill well placement based on the undepleted and undrained regions. The field application clearly demonstrates a systematic approach to optimal well placement in tight gas reservoirs.

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