Porosity-permeability relationships in the framework of hydraulic flow units can be used to characterize heterogeneous reservoir rocks. Porosity is a volumetric parameter whereas permeability is a measure of a rock's flow properties and depends on pore distribution and connectivity. Thus zonation of a reservoir using flow zone indicators and the identification of flow units can be used to evaluate reservoir quality based on porosity-permeability relationships. In the present study, we attempt to make a quantitative correlation between flow units and well log responses using fuzzy logic in the mixed carbonate-clastic Asmari Formation at the Ahwaz oilfield, South Iran. A hybrid neuro-fuzzy approach was used to verify the results of fuzzy modelling. For this purpose, well log and core data from three wells at Ahwaz were used to make an intelligent formulation between core-derived flow units and well log responses. Data from a separate well was used for evaluation and validation of the results. The results of this study demonstrate that there is a good agreement between core-derived and fuzzy-logic derived flow units. Fuzzy logic was successful in modelling flow units from well logs at well locations for which no core data was available.