The importance of evaluating well productivity after hydraulic fracturing can not be overemphasized. This has necessitated the improvement in the quality of rate and pressure measurements during flowback of multistage fractured wells. Similarly, there has been corresponding improvements in the ability of existing transient models to interpret multiphase flowback data. However, the complexity of these models introduces high uncertainty in the estimates of resulting parameters such as fracture pore-volume, half-length and permeability. This paper proposes a two-phase tank model for reducing parameter uncertainty and estimating fracture pore-volume independent of fracture geometry.This study starts by using rate-normalized pressure plots to observe changes in fluid flow mechanisms from multistage fractured wells. The fracture "pressure supercharge" observations form the basis for developing the proposed two-phase tank model. This model is a linear relationship between rate normalized pressure and time, useful for interpreting flowback data in wells which show pseudo steady-state behavior (unit slope on log-log rate normalized-pressure plots). The linear relationship is implemented on a simple monte-carlo spreadsheet. This is then used to estimate and conduct uncertainty analysis on effective fracture pore-volume, using probabilistic distributions of average fracture compressibility, and gas/water saturations respectively. Also, the proposed model investigates the contributions of various drive mechanisms during flowback including fracture closure, gas expansion and water depletion.Application of the proposed tank model to flowback data from fifteen shale gas and tight oil wells estimates the effective fracture pore-volume and initial average gas saturation in the active fracture network. The results show that fracture pore-volume is most sensitive to fracture closure compared to gas expansion and water depletion, making fracture closure the primary drive mechanism during early flowback periods. Also, the initial average gas saturation for all wells is less than twenty percent. The parameters estimated from the proposed model could be used as input guides for more complex studies (such as discrete fracture network modeling and transient flowback simulation). This reduces the number of unknown parameters and uncertainty in output results from complex models.