Utilizing Facies and lithofacies thin sections and laboratory experimental techniques for Late Cenomanian-Early Turonian carbonate reservoir characterization in an Iraqi oilfield, Iraq, Middle East region

Abstract Mishrif Formation holds significant importance as an oil-producing stratum, originating from shallow marine settings during the Late Cenomanian to Early Turonian period in southern Iraq. This study focuses on two specific wells, Rt2 and Rt5 in Ratawi oilfield, chosen as primary subjects. Collectively, more than 200 core samples were meticulously gathered from these wells and subjected to thin section analysis. Petrographic scrutiny of the thin sections unveiled that Mishrif Formation encompasses four primary facies and an additional ten secondary facies, which were deposited across a broad spectrum of environments, spanning from shallow marine to shallow or open lacustrine settings. The analysis of thin sections further confirmed the existence of diagenetic processes that influenced the rock properties of the formation. Among these processes were dissolution, cementation, and compaction, all contributing to the alteration of porosity characteristics. Notably, interparticle porosity, vuggy porosity, and intrafossil porosity emerged as the predominant forms of porosity within the formation. Distinct diagenetic environments were identified based on the findings, including shallow marine, mixed, and surface settings. The study revealed an evolution of facies traits and diagenetic processes towards the Rt5 well. Important parameters such as porosity, permeability and water saturation are determined. Correlations are used to assess permeability in uncored wells because direct measurement techniques, such as core analysis and well testing, are costly. Understanding fluid flow in the formation is aided by an exponential equation with R-squared values evaluating the fit between core permeability and porosity. By breaking the reservoir up into units and minimizing heterogeneity, the FZI approach provides the best regression. The usual method for predicting permeability is to divide well data into homogeneous subgroups according to hydraulic flow units and microfacies. By enhancing permeability projections and decreasing the requirement for extensive coring, porosity-permeability analysis offers insightful information. The novelty in this paper lies in identifying good reservoirs, understanding their extensions, determining the direction of facies development, and knowing locations where facies reservoir properties are expected to be present.