3D pixel-based stochastic lithofacies modeling in a tidal sandstone reservoir

Abstract

The geological facies modeling is a crucial problem in the overall reservoir characterization as it affects the reservoir heterogeneities and fluid flow performance prediction. The main purpose of the research is to adopt the stochastic lithofacies modeling in a tidal sandstone reservoir (Main Pay) of South Rumaila Oil Field to build the geological structure of the reservoir. Based on the core measurements, the reservoir has three main lithofacies: Sand, Shaly Sand, and Shale as the literature indicates that it encompasses mainly of sandstone with some interbedded shale zones. In addition, the main pay formation was deposited in a tidal sand-rich environment that the sand channels are stacked and prevailed everywhere across the formation. The Sequential Indicator Simulation (SISIM) has been used to build the categorical image, pixel by pixel considering the nonparametric condition distribution. SISIM depends on the variogram to address and model the variation between any two spatial points from the available data. Therefore, 12 different variograms have been built given the three lithofacies in four different directions: 0°, 45°, 90°, and 135° The resulted lithofacies models given the three lithotypes have indicated good matching with the original formation depositional environment of tidal dominated and sand-rich environment