This study is concerned with making comparison in using different geostatistical methods for porosity distribution of upper shale member - Zubair formation in Luhais oil field which was chosen to study.
Kriging, Gaussian random function simulation and sequential Gaussian simulation geostatistical methods were adopted in this study. After preparing all needed data which are contour map, well heads of 12 wells, well tops and porosity from CPI log. Petrel software 2009 was used for porosity distribution of mentioned formation in methods that are showed above. Comparisons were made among these three methods in order to choose the best one, the comparing criteria was according to different statistical information and variograms analysis of entered porosity which was scaled up and modeled. The best method gave porosity distribution in model closest to enter porosity that represent real porosity of Zubair formation.
The comparison proved that sequential Gaussian simulation is the best model of porosity distribution followed by Gaussian random function simulation and kriging methods respectively. Based on the results obtained, it was concluded that the distribution accuracy of the porosity or other petrophysics properties is one of the main factors that affect building correct geological model that represents the base of reservoir model and also pore volume (Oil reserve) value was affected by geostatistical methods variation.