Abstract

As a powerful technique for quantitative production data analysis, type curves play an essential role in estimating reservoir and fracture properties. However, two-phase flow after hydraulic fracturing furthers the governing equation's nonlinearity and introduces substantial errors in type-curve analysis, which must be extended to two-phase systems. This study presents a new type-curve method to characterize hydraulic fracture (HF) attributes and dynamics by analyzing two-phase flowback data from multi-fractured horizontal wells (MFHWs) in hydrocarbon reservoirs. The proposed method is, to the best of our knowledge, the first semi-analytical type-curve approach that not only considers the two-phase flow in both fracture and matrix, but also takes variable BHP and rate conditions. Meanwhile, a new set of dimensionless groups are proposed to incorporate the complexity of the coupled two-phase flow in fracture and matrix into one unique curve, rather than families of curves, which significantly reduces the non-uniqueness issue of type-curve matching for MFHWs. Unlike other two-phase type curves, the pressure and saturation dependent parameters in the dimensionless groups are rigorously evaluated at the average properties within the HF based on the material balance equations. The accuracy of the proposed method is tested using the synthetic data generated from six numerical simulation cases for shale gas and oil reservoirs. The numerical validation confirms the unique behavior of type curves during fracture boundary dominated flow and verifies the accuracy of the type-curve analysis in the characterization of fracture properties. For field application, the proposed method is applied to two MFHWs in Marcellus shale gas and Eagle Ford shale oil. The agreement of interpreted results between the proposed method and straight-line analysis not only demonstrates the practicality in field application but also illustrates the superiority of the type-curve method as an easy-to-use technique to analyze two-phase flowback data.

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