Prediction of SRV and Optimization of Fracturing in Tight Gas and Shale Using a Fully Elasto-Plastic Coupled Geomechanical Model

摘要

Hydraulic fracturing is essential for economical development of tight gas and shale gas reservoirs. Current techniques are unable to predict the SRV dependence on frac job and rock mechanics parameters, which precludes any meaningful optimization. In our previous work on the SRV propagation prediction by means of combined tensile/shear fracturing model, the applications showed relatively narrow, focused SRV that resembled behavior dominated by a single fracture. In this work, we significantly improved the model by implementing rigorous full Newton elasto-plastic solution of fracturing problems by pseudo-continuum technique. The results reveal interesting features of complex fracturing occurring in tight formations, which are in broad agreement with the shapes of SRV’s obtained from microseismic imaging. Flexibility of the code to select either tensile or shear fracturing mechanism or combination of both allows various scenarios to be examined. Different cases of 2-D and 3-D simulations will be presented which demonstrate some important features of the process. First, it is found that a wide SRV can result in cases where initial reservoir conditions are close to shear fracturing point such as in formations with microfractures, partially cemented natural fractures and abnormally high initial pore pressure. The SRV width is found to depend on the horizontal stress contrast as expected. Second, wide SRV growth is associated with constant or increasing pumping pressure for further failed zone growth due to the loss of elastic coupling by off-planar failure propagation. Further, under high injection pressure, an efficient fracture elasto-plastic constitutive model developed can drive both maximum and minimum effective stresses to zero or tensile and therefore creation of tensile fracture can be predicted simultaneously with shear fracturing. This will then provide means of modeling proppant transport. The new model is a significant step towards development of an integrated predictive tool for the optimization of shale gas development.