The forefront stage in any production plan in petroleum industry is exploration which has always been considered as a risky, costly and time consuming task. Due to significant drilling costs and time required for any petroleum drilling program, application of valid and accurate estimation methods for petrophysical parameters is inevitable and highly demanded. In the current study, exploratory data from a number of 11 exploratory wells including 3 cored ones from an oil field in south-west Iran were available. The structural settings of the reservoir had been previously determined to be an anticline with a length of 12 kilometers and width of 700 meters by petroleum geologists. The most important petrophysical parameters for reservoir characterization employed in this study were porosity, water (oil) saturation, permeability and capillary pressure. Based on permeability distribution throughout resevoir, it was found that there exists two permeability populations.The overal fitting between estimated permeability versus measured ones on validating data was quatified through R-square (R=correlation coefficient) to be 97.72% which is considerd as appropriate. Through obtaining suitable model using Harris and Goldsmith (2001) capillary pressure model, predicting regression models with great agreement with cored sample data for displacement capillary pressure and irreducible water saturation were developed. Applying the newly developed mathematical models to the unsampled exploratory wells and extending the estimated petrophysical parameters using 3D geostatistical estimation methods, the block 3D solid models were constructed for each petrophysical parameter in part of reservoir estimation space spanning well positions. Statistics from 3D solid models show that the average porosity coincides with sandstone and shale lithologes whereas limestone (with some minor areas covered by dolomite) has shown both low and high porosity behaviour as a result of developed joints and fractures. The permeability gets its highest values where highly jointed and fractured porosity limestones are present. Low capillary pressure areas coincides with areas having fractured porosities with suitable pore throat size. Also areas with low permeability represent shale, dolomite or compacted-nonfractured limestones having low porosity. Finally the total hydrocarbon volume above 5% porosity cut off value was estimated to be 11051800±3344580 cubic meters. To facilitate using the models developed through this study, an algorithm for the systematic estimation procedure was designed and a prototype program in Matlab environment was developed.