Abstract

This paper summarizes findings from a one-year study sponsored by seven operators and service companies to investigate interpretation of diagnostic fracture injection tests (DFIT’s). The study combined computational modeling, a diverse collection of field data, and operator experience. DFIT simulations were performed with a three-dimensional hydraulic fracturing, wellbore, and reservoir simulator that describes fracture propagation, contacting of the fracture walls, and multiphase flow. Interpretation procedures were applied to estimate stress, permeability, and pressure from the synthetic data. The interpretations were compared to the simulation input parameters to evaluate accuracy. Based on the results, new techniques were developed, existing techniques were refined, and an overall interpretation protocol was developed. The techniques were applied to interpret over thirty field DFIT’s drawn from shale plays across the US and Canada, and the methods were evaluated in the context of operator experience. The results are applicable to fracturing tests in formations with permeability ranging from nanodarcies to 10s of microdarcies. The minimum principal stress is estimated by identifying the ‘contact pressure’ when the fracture walls come into contact, causing fracture compliance and system storage coefficient to decrease. After the walls come into contact, the pressure transient is controlled by the interplay of changing fracture compliance, deviation from Carter leakoff, and multiphase flow. The contact pressure is slightly greater than the minimum principal stress. It can be identified from either a plot of dP/dG or a relative stiffness plot. Permeability is estimated using the G-function method, a newly developed h-function method that accounts for deviation from Carter leakoff, and impulse linear flow. These three methods, which are based on linear flow geometry, require an estimate of fracture area. We derive equations for estimating area using mass balance equations, accounting for wellbore storage and fluid leakoff. The results from field data show that impulse linear permeability estimates are usually 2-5 times lower than estimates derived from the G-function and h-function methods, apparently indicating a difference between effective permeability during leakoff and permeability during flow of reservoir fluid through the formation. Impulse radial flow regime may be used for estimating permeability, but should be used with caution. Simulation results indicate that a variety of processes can cause an apparent radial trend that is not actually radial flow. Simulations and field data indicate that ‘false radial’ is very common in gas reservoirs and, if applied, leads to a large overestimate of permeability. Production history matching using overestimated permeability will underestimate fracture length, potentially resulting in suboptimal choices for well and cluster spacing.