Production of unconventional oil and gas resources has played a significant role on the global energy supply, of which tight oil and gas reservoirs are drawing greater focus. The key enabler behind tight oil and gas production has been multi-stage hydraulic fracturing along extended reach horizontal wells. Despite many advances in multistage fracturing, it still remains unclear how to model the hydraulic fracturing process to provide the basis to optimize and predict the properties of fracture networks and associated enhancement of fluid production. This is especially difficult since it is not possible to directly image the fracture network since the length scales of the network can be relatively small. In typical reservoir simulation practice, the conventional way to represent the hydraulic fracture is to place transverse plane around the horizontal well – this means that the user has prescribed the orientation and length scale of the fracture before the simulation has started. In the research documented here, we explore a dynamic fracturing approach that uses a dilation-recompaction model in a reservoir simulator to model hydraulic fracturing. The key strength of the approach is that the geometry and length scale of the fracture is not prescribed a priori. This means that the model can be relatively easily constructed and matched to field data. The results of the simulation show that dilation-recompaction model is capable of modeling the hydraulic fracturing process prior to the flow-back and production. The oil, gas, and water rates of the model are well matched to the field data and the extent of the fractured zone predicted by the model is reasonable. A sensitivity analysis using the history-matched model reveals that the design of hydraulic fracturing operation suggests that a larger number of stages and fracture fluid volume injected will raise oil and gas rates, but it remains unclear if the incremental oil and gas will provide enough revenues to offset the additional costs from increases of stages and fluid injection volume.