The Mishrif Formation is one of the most important geological formations in Iraq consisting of limestone, marl, and shale layers since it is one of the main oil producing reservoirs in the country, which contain a significant portion of Iraq's oil reserves. The formation has been extensively explored and developed by the Iraqi government and international oil companies, with many oil fields being developed within it. The accurate evaluation of the Mishrif formation is key to the successful exploitation of this field. However, its geological complexity poses significant challenges for oil production, requiring advanced techniques to accurately evaluate its petrophysical properties.

   This study used advanced well-logging analysis techniques, including mineralogical inversion with the Quanti-Elan model employed in Schlumberger's Techlog software to evaluate this formation. The lithology, clay volume, porosity, permeability, and hydrocarbon saturation data were obtained from the open hole logging of three wells in a southern Iraqi oil field. The environmental correction was applied for open-hole logging tools, and the primary mineral of the formation was determined using porosity log cross-plotting. Pickett plot technique was utilized to determine water resistivity and Archie's parameters, and the reconstruction log was generated based on volumetric and response parameters for each component. Based on thorough analysis, the clay volume of the Mishrif formation is estimated to be about 10%, which is a common value for this rock type. The porosity was computed based on the total fluid volume, ranging from 11% to 14%, and water saturation was determined using Archie's equation. The final results of the volume of each component for rock and fluid are presented using computer programming interpretation. The results of this study provide valuable insights into the petrophysical properties of the Mishrif formation and are expected to inform for better interpretation and evaluation of petrophysical properties of similar formations, which is essential for optimum field development planning as well as minimising the uncertainties.