In this study, the non-intrusive embedded discrete fracture model (EDFM) in combination with the Oda method are employed to characterize natural fracture networks fast and accurately, by identifying the dominant water flow paths through spatial connectivity analysis. The purpose of this study is to present a successful field case application in which a novel workflow integrates field data, discrete fracture network (DFN), and production analysis with spatial fracture connectivity analysis to characterize dominant flow paths for water intrusion in a field-scale numerical simulation. Initially, the water intrusion of single-well sector models was history matched. Then, resulting parameters of the single-well models were incorporated into the full field model, and the pressure and water breakthrough of all the producing wells were matched. Finally, forecast results were evaluated. Consequently, one of the findings is that wellbore connectivity to the fracture network has a considerable effect on characterizing the water intrusion in fractured gas reservoirs. Additionally, dominant water flow paths within the fracture network, easily modeled by EDFM as effective fracture zones, aid in understanding and predicting the water intrusion phenomena. Therefore, fracture clustering as shortest paths from the water contacts to the wellbore endorses the results of the numerical simulation. Finally, matching the breakthrough time depends on merging responses from multiple dominant water flow paths within the distributions of the fracture network. The conclusions of this investigation are crucial to field modeling and the decision-making process of well operation by anticipating water intrusion behavior through probable flow paths within the fracture networks.