Abstarct: The influence of fracture network on quality of reservoir, emphasize the importance of study of fractured reservoirs. The main gold of study these reservoir, is building fracture models. Fractures modeling results use as Input data for flow simulation and analysis. Several approaches were proposed for fracture modeling that all of them have advantage and disadvantage in data analysis and fracture modeling. One of them is “Discrete Fractures network” model. Discrete fracture network (DFN) models portray fractures and their connectivity very differently from other methods.These models more realistically model the connectivity of the faults and joints that give rise to reservoir-scale and well-scale non-continuum flow behavior.We are going to study fractures of one of the Southwest Oilfields of Iran by discrete fracture network modeling.The main aspect of present study is discussion about improve fractures model using fractured zone data recorded by petrophysicalfullset. For this goal, first fracture network were build using image logs (model 1). In this stage, fracture intensity was upscaled to all of reservoir. Next, fracture intensity logs using fractured data zone were computed.In follow, The Intensity fracture obtained through the modeling was comparedwith the results of “petrophysicalfullset” and really intensity fracture in one of the wells.As for the difference between three logs, this conclusion was obtained that with the conflation of image log data and petrophysical logs data, uncertainty can be reduced. Therefore model 2 was build using this method. Comparing with real, model 2 has better function in fractures modeling.For improvement quantifying, the cost function were defined.Results have shown that fractures model using image log and petrophysical fullest data enhancedcertitude 9% more than fracture model using image log data.