Characterization of naturally fractured reservoirs (NFR) is a complex process which requires the collaboration and team work of geologists, geophysicists and reservoir engineers. Due to a fractured reservoirs heterogeneous nature, some understanding of the rock properties and associated fracture system is required before undertaking a full field study. To gain this knowledge, a characterization of the field and the fracture network should be performed, to identify the effects the fractures have on the flow of fluids and ultimate hydrocarbon recovery. Fracture characterization was traditionally done with data acquired at the well using cores and image logs or other approaches which combined the known geological and structural data with geostatistical methods. Recent developments in both seismic acquisition and processing, along with the growth of computer-aided techniques has led to numerous analytical tools being developed. Modern day fuzzy logic and neural networks are also tools which play a major role in some approaches, ultimately resulting in maps of fracture intensity. Today, there are many different manners in which the characterization of fractured reservoirs is being performed. Two main stream approaches have been identified. Based on available literature, in-depth descriptions and workflows have been created to demonstrate the functionality and integration of data for the purpose of reservoir modeling.