Natural fractures provide an important reservoir space and migration channels for oil and gas reservoirs and control the reservoir potential. Therefore, it is essential to understand the methods for identifying accurate reservoir permeability and characterizing reservoir fractures. In particular, using conventional measurements to identify permeability and characterize fractures is very expensive. While using conventional logging data is very challenging, and an efficient characterization correlation method is urgently needed. In this paper, we have evaluated reservoir potential based on the sensitivity of sonic scanner tools to fluid mobility, maximum stress direction, and fractures presence. This tool provides a continuous estimation of these important parameters along the studied formation using a real field data. Dispersion behavior based on the difference between the maximum and minimum energy of the studied formation is used to detect reservoir heterogeneity and anisotropy. Dispersion analysis shows the presence of inhomogeneous anisotropy in several intervals along the studied formation. The methodology used in this paper provides an accurate estimation of reservoir permeability varies from 1 to 100 md. Also, the application of this technique shows an accepted percent error of reservoir permeability estimation reaches to 7% when compared to laboratory core measurements. The average direction of the maximum horizontal stress in the studied formation is detected to be NW10 to N16E. The study results prove that the proposed technique is effective for the identification of important reservoir properties in the oil industry.
