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In this paper, a case study in a fractured carbonate reservoir is presented to demonstrate the approach of fracture modeling using fracture intensity volume. Fracture information described from well data and fracture prediction data generated from pre-stack seismic data are both used to establish discrete fracture model. FMI logs, mud losses, log interpretation results and production data are used to describe fracture characteristics on each well. Fractures are divided into 4 sets based on fracture scales, fracture dip and strike interpreted from FMI log. Fracture density logs for each set is generated separately, and each set of logs is used separately for fracture modeling. Seismic attribute of pre-stack azimuthal anisotropy is generated. This attribute volume is compared with FMI interpreted fracture density along wellbores for over 120 wells. The consistency of seismic attribute with well data is good for 90 per cent of wells. Hence the seismic attribute of pre-stack azimuthal anisotropy is used as fracture intensity volume for fracture prediction. A DFN model is established for each set of fractures using FMI interpreted fracture density as hard data and the seismic based fracture intensity volume as constraining data. Fracture properties are calculated based on discrete fracture network and calibrated by well test analysis.