Evaluation of Water Saturation in a Low-Resistivity Pay Carbonate Reservoir Onshore Abu Dhabi: An Integrated Approach

Abstract

Abstract Characterization and fluid quantification of Carbonate reservoirs looks more challenging than those of sandstone reservoirs. The determination of accurate hydrocarbon saturation is more tasking due to their complex and heterogeneous pore structures, and mineralogy. Traditionally, resistivity logs are used to identify pay intervals due to the resistivity contrast between oil and water. However, when pay intervals exhibit low resistivity, such logs exhibit low confidence in the precise determination of the hydrocarbon saturation. Few Middle-Eastern reservoirs are categorized as low resistivity pay, where resistivity based log analysis results in high water saturation. However, downhole fluid analysis identifies mobile oil, and the formation flows dry or nearly dry oil during production tests. This makes resistivity based saturation computation questionable. Because of the complexity of low resistivity pay (LRP), its cause should be determined prior to applying a solution. Several reasons were identified to be responsible for this phenomenon- among which are the presence of micro-porosity, fractures, paramagnetic minerals, and deep conductive borehole mud invasion. Integration of Thin section, Nuclear magnetic resonance (NMR) and Mercury injection capillary pressure (MICP) data from the studied formation indicated the presence of micropores network. This paper discusses the observed variations in quantifying water saturation in LRP interval and the related discrepancies between the resistivity and non-resistivity based techniques. The non-resistivity based methods, used in the course of this study, are coined from sigma log measurement and core data, either capillary pressure-based (MICP, Centrifuge, and Porous plate), or direct from Dean-Stark measurements. The interpretation process considered water saturation derived from resistivity measurement and core data combined with production test information. The combination of several water saturation determination approaches captured the uncertainty and improved our understanding of the reservoir properties. This enhanced our capability to develop a robust and reliable saturation model. The integration of data from these various sources added confidence to the estimation of water saturation in the studied field and thus, improved reserves estimation and reservoir simulation for accurate history matching, production forecasting and optimized field development plan.