Although many scholars have put forward the methods and models to predict the stimulated reservoir volume (SRV), the mathematical models do not reflect well the mechanism of SRV development. In addition, the effects of relative fracture treatment and reservoir parameters on different stimulation areas are not well understood. During the process of hydraulic fracture propagation, fracturing fluid leak-off from the main fracture due to the activation of natural fractures can elevate the reservoir pore pressure, resulting in shear slippage and tensile failure of the natural fractures and, finally, in microseismic events. Different stimulation regions, including tensile failure zone, shear failure zone, and swept region, may co-exist along the activated natural fracture. In this study, a new mathematical model was presented based on the shear slippage and tensile failure criterion of weakness plane, hydraulic fracture propagation model, mechanical conditions of natural fracture activation, fluid diffusivity equation, and using a shear dilation model to characterize the reservoir permeability variation after shear slippage of the natural fractures, so as to better describe the growth of SRV. The model was also verified by matching field microseismic monitoring data. Then, the effects of azimuth angle and horizontal principal stress difference on the shear and tensile failure pressure of natural fractures, permeability enhancement, and critical net pressure of main fracture to activate natural fractures were illustrated. The impacts of treatment fluid viscosity, natural fracture azimuth angle, and horizontal stress difference on the reservoir pore pressure, SRV shape distribution, different SRV sizes, and SRV bandwidth and length were also analyzed. The results indicated that increasing the horizontal stress difference decreased the tensile failure area but increased the shear slippage zone sharply. Both shear and tensile failure regions decreased on increasing the natural fracture azimuth angle from 30° to 50°. Increasing the fluid viscosity from 1 to 10 mPa·s expanded the size of the tensile failure zone but reduced the shear slip zone.
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This study was supported by the National Natural Science Foundation of China (51404207) and the National Science and Technology Major Project (2016ZX05052 and 2016ZX05014). This support is gratefully acknowledged.
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Conflict of interest
The authors declare no conflicts of interest regarding the publication of this study.
Cheng W, Jin Y, Chen M (2015) Reactivation mechanism of natural fractures by hydraulic fracturing in naturally fractured shale reservoirs. J Nat Gas Sci Eng 23:431–439CrossRefGoogle Scholar
Chong HA, Dilmore R, Wang JY (2014) Development of innovative and efficient hydraulic fracturing numerical simulation model and parametric studies in unconventional naturally fractured reservoirs. J Unconvent Oil Gas Resour 8(4):25–45Google Scholar
Cipolla CL (2009) Modeling production and evaluating fracture performance in unconventional gas reservoirs. J Pet Technol 61(9):84–90CrossRefGoogle Scholar
Dahi-Taleghani A, Olson JE (2011) Numerical modeling of multi-stranded hydraulic fracture propagation: accounting for the interaction between induced and natural fractures. Spe J 16(3):575–581CrossRefGoogle Scholar
Ge J, Ghassemi A (2012) Stimulated reservoir volume by hydraulic fracturing in naturally fractured shale gas reservoirs. American Rock Mechanics AssociationGoogle Scholar
Ghassemi A, Zhou XX, Rawal C (2013) A three-dimensional poroelastic analysis of rock failure around a hydraulic fracture. J Pet Sci Eng 108(3):118–127CrossRefGoogle Scholar
Guo J, Liu Y (2014) Opening of natural fracture and its effect on leakoff behavior in fractured gas reservoirs. J Nat Gas Sci Eng 18:324–328CrossRefGoogle Scholar
Hossain MM, Rahman MK, Rahman SS (2002) A shear dilation stimulation model for production enhancement from naturally fractured reservoirs. Spe J 7(2):183–195CrossRefGoogle Scholar
Ji L, Settari A, Sullivan RB (2009) A novel hydraulic fracturing model fully coupled with geomechanics and reservoir simulation. Spe J 14(3):423–430CrossRefGoogle Scholar
Kim J, Moridis GJ (2015) Numerical analysis of fracture propagation during hydraulic fracturing operations in shale gas systems. Int J Rock Mech Min Sci 76:127–137CrossRefGoogle Scholar
Kresse O, Weng X (2013) Hydraulic fracturing in formations with permeable natural fractures. Int Soc Rock Mech Rock EngGoogle Scholar
Nagel NB, Sanchez-Nagel MA, Zhang F, Garcia X, Lee B (2013) Coupled numerical evaluations of the geomechanical interactions between a hydraulic fracture stimulation and a natural fracture system in shale formations. Rock Mech Rock Eng 46(3):581–609CrossRefGoogle Scholar
Nassir M, Settari A, Wan RG (2014) Prediction of stimulated reservoir volume and optimization of fracturing in tight gas and shale with a fully elasto-plastic coupled geomechanical model. Spe J 19(5):771–785CrossRefGoogle Scholar
Palmer I, Moschovidis JCZ, Ponce J (2009) Natural fractures influence shear stimulation direction. Oil Gas J 107(12):37–43Google Scholar
Palmer ID, Moschovidis ZA, Schaefer A (2013) Microseismic clouds: modeling and implications. Spe Prod Oper 28(2):181–190Google Scholar
Rutqvist J, Rinaldi AP, Cappa F, Moridis GJ (2013) Modeling of fault reactivation and induced seismicity during hydraulic fracturing of shale-gas reservoirs. J Pet Sci Eng 107(4):31–44CrossRefGoogle Scholar
Shahid ASA, Wassing BBT, Fokker PA, Verga F (2015) Natural-fracture reactivation in shale gas reservoir and resulting microseismicity. J Can Pet Technol 6(54):450–459CrossRefGoogle Scholar
Taleghani D, Olson JE (2011) Numerical modeling of multi-stranded hydraulic fracture propagation: accounting for the interaction between induced and natural fractures. SPE J 16(3):575–581CrossRefGoogle Scholar
Zhang J, Biao FJ, Zhang SC, Wang XX (2014) A numerical study on interference between different layers for a layer-by-layer hydraulic fracture procedure. Pet Sci Technol 32(12):1512–1519CrossRefGoogle Scholar