Flowback Fracture Closure: A Key Factor for Estimating Effective Pore Volume
- Obinna Ezulike (University of Alberta) | Hassan Dehghanpour (University of Alberta) | Claudio Virues (Nexen ULC) | Robert V. Hawkes (Trican Well Service Ltd) | R. Steven Jones Jr. (Newfield Exploration)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- October 2016
- Document Type
- Journal Paper
- 567 - 582
- 2016.Society of Petroleum Engineers
- Probabilistic uncertainty reduction, Fracture closure effects, Two Phase Flowback Tank Model, Fracture geometry independent estimates, Representative effective fracture pore-volume
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The importance of evaluating well productivity after hydraulic fracturing cannot be overemphasized. This has necessitated the improvement in the quality of rate and pressure measurements during flowback of multistage-fractured wells. Similarly, there have 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 (PV), half-length, and permeability. This paper proposes a two-phase tank model for reducing parameter uncertainty and estimating fracture PV independent of fracture geometry. This study starts by use of rate-normalized-pressure (RNP) 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 RNP and time, useful for interpreting flowback data in wells that show pseudosteady-state behavior (unit slope on log-log RNP 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 PV by use of probabilistic distributions of average fracture compressibility and gas/water saturations. Also, the proposed model investigates the contributions of various drive mechanisms during flowback (fracture closure, gas expansion, and water depletion) by use of quantitative drive indices similar to those used in conventional reservoir engineering. Application of the proposed tank model to flowback data from 15 shale-gas and tight-oil wells estimates the effective fracture PV and initial average gas saturation in the active fracture network. The results show that fracture-PV estimation is most sensitive to fracture closure compared with 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 20%. 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.
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