Rock selection in modeling and simulation studies is usually based on two techniques; routinely defined rock types and those defined by special core analysis (SCAL). The challenge in utilizing these two techniques is that they are frequently assumed to be the same, but in practice, static rock-types (routinely defined) are not always representative of dynamic rock-types (SCAL defined) in the real reservoir. There is also no significant link between these two techniques. To fill this gap, we integrate the well log data for identification of the optimal number of rock-types, and SCAL data with its high interpretive potential in a given reservoir zonation. In this paper, we propose a method in one of Iranian offshore oil reservoir with a tight carbonate formation for dynamic rock type characterization. In this method, with the integration of well logs and core description data using multivariate statistical methods, different static rock-types can be identified, but these rock types cannot be assigned for fluid flow simulation. So, with our approach based on capillary pressure curves, different flow behavior can be classified. This technique can be done by using integration of similar capillary pressure curves due to the inlet pressure corresponding to the log parameters. Finally, with integration of capillary pressure and well log data, two different dynamic rock-types with distinct flow behavior were identified. This method can be used for the development of rock-type characterization and deriving of saturation height functions for calculation of initial water saturation in any heterogonous reservoir and it is an applicable solution for inputs in Geomodel and also simulation models.