Abstract

Oolitic grainstones can contain significant hydrocarbon reserves. Due to variations in sedimentary processes and diagenetic alteration, the porosity and permeability values of these deposits are highly variable. We identified potential reservoir units in the Lower Triassic Khartam Member of the Upper Khuff Formation in central Saudi Arabia using an outcrop analog model by incorporating outcrop porosity and permeability information.Six major surfaces representing fourth-order sequence boundaries were identified in outcrop, and these separate the five zones in the model. In terms of depositional environments, these are defined as Zones 1 and 2 (subtidal and sand sheets deposits in a shoal complex), Zones 3 and 4 (sand sheets and lenses deposits in a back shoal), and Zone 5 (tidal flat). The population of lithofacies with in each zone in the three dimensional (3D) outcrop model was performed separately using a different geostatistical algorithm. The resulting 3D facies model adequately illustrates the continuity of beds and fairly represents the stratigraphic architecture observed in outcrop. The 3D volume of the outcrop model was subdivided into three broad stratigraphic intervals. The lower interval (Zones 1 and 2) was deposited during a rapid sea-level rise at the Permian–Triassic transition and consists dominantly of oolitic units with oomoldic and interparticle porosity. The middle interval (Zones 3 and 4) was deposited during an interval of rapid sea-level fluctuation and is characterized by the appearance of marine fauna after a long-term extinction in the lower Triassic interval. The dominant porosity types within this interval are moldic, interparticle, and intraskeletal. The upper interval (Zone 5) was deposited during a major sea-level regression. This interval contains a significant amount of early diagenetic dolomite and is dominated by interparticle and intercrystalline porosity.The results demonstrate that including porosity values from outcrop measurements in a 3D outcrop facies model can provide more accurate visualizations of reservoir units. This methodology could be used to predict reservoir potential in analogous carbonate reservoirs.

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