Characterizing the reservoir accurately and understanding its rock’s composition is essential in predicting performance and determining reservoir designs. In this study, the carbonate Khasib formation from the late Cretaceous period for x oil field- southern Iraq has been examined characterizing. To achieve this, different characterization techniques were utilized. Firstly, using the flow zone indicator method revealed five hydraulic flow units (HFUs) of the Khasib formation. Every HFU represents a particular quality of reservoir rock. HFU1 is the one that refers to poor quality, while bad-quality reservoir rock is displayed as HFU2. HFU3 and HFU4 signify the intermediate and good reservoir rock quality respectively. The last hydraulic flow unit was of the highest quality reservoir rock which is denoted as HFU5. Additionally, we utilized cluster analysis to identify five distinct rock types within the Khasib formation. These rock types were labeled as RT-1 (the best reservoir rock type), RT-2 (good reservoir rock type), RT-3 (intermediate reservoir rock type), RT-4 (poor rock type), and RT-5 (very poor rock type). In addition, the recognition of five different HFUs that reflected the physical characteristics unique to each reservoir rock was achieved using Winland’s approach. Rock properties inside the reservoir are classified to HFU1 for best rocks, then HFU2 denotes good rock qualities through a medium one labeled as HFU3 while later HFU4 indicates poor quality, and the poorest quality is marked as HFU5. Finally, Lucia's classification for carbonate rock was employed as another analyzing rock quality method. Utilizing this technique reveals three distinct rock types within the Khasib formation. RC1 is the microfacies of grain stone, RC2 is the representative of pack-stone microfabrics and RC3 denotes muddy materials. The final rock types (facies) for Khasib formation can be identified according to the incorporation of the different characterization methods which can be utilized to create a realistic three-dimensional rock type model and distribute the properties based on the rock type.
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