A Semi-Analytical Forecasting Method for Unconventional Gas and Light Oil Wells: A Hybrid Approach for Addressing the Limitations of Existing Empirical and Analytical Methods

Abstract The rapid pace of exploitation of unconventional gas and light oil (UG/ULO) plays in North America has necessitated the development of new production forecasting methodologies to aid in reserves assessment, capital planning and field optimization. The generation of defendable forecasts is challenged not only by reservoir complexities but also by the use of multi-fractured horizontal wells (MFHWs) for development. In this work, we have developed a semi-analytical method that provides a solid theoretical basis for forecasting. The technique is analytical in that it uses the methods of Agarwal (2010) to calculate contacted oil- and gas-in-place (COIP/CGIP) from production rates, flowing pressures and fluid properties. The rate-normalized pressure (for liquids) or pseudopressure (for gas) derivative (RNP') is a key component of the calculation. The technique is also empirical in that an empirical function is fit to the resulting COIP/CGIP curve versus time. Although the method is flexible enough that any equation can be used to represent the COIP/CGIP curve, and hence the sequence of flow-regimes exhibited by MFHWs, the equation must be capable of being integrated to allow extraction of rate-normalized pressure or pseudopressure (RNP). The stabilized COIP/OGIP during boundary-dominated flow must be specified for forecasting – thereafter, the method uses a material balance simulator to model boundary-dominated flow. Hence, if the well is still in transient flow, a range in forecasts may be generated, depending on the assumed stabilized COIP/OGIP. Our new semi-analytical method addresses some of the current limitations of empirical and fully analytical (modeling) approaches. Empirical methods, which have been adapted to account for long transient and transitional flow periods associated with ultra-low permeability reservoirs, lack a theoretical basis, and therefore input parameters may be difficult to constrain. However, empirical methods are simple to apply and require a minimum amount of data for forecasting. Analytical models, while better representing the physics, nonetheless require additional reservoir and hydraulic fracture data which may not be available on every well in the field. The semi-analytical method proposed herein is intended to bridge the gap between empirical and modeling-based approaches – it is more rigorous than purely empirical methods, while requiring less data than fully analytical techniques. The new method is tested against simulated and field cases (tight oil and shale gas). Although we have used a simple power-law function to represent COIP/OGIP curve, which appears adequate for the cases studied, we note that wells exhibiting long transitional (e.g. elliptical/radial) will likely require a different functional form.

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