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The aim of this study is to statistically analyze the impact of diagenesis on reservoir-quality and to propose a specific workflow that will simulate the spatial distribution of rock textures, diagenetic trends, and reservoir properties by using material and data from 10 wells in a field from offshore Abu Dhabi (Jurassic Arab D Member), United Arab Emirates. Five parasequence sets (PS 1-5) are distinguished from Arab D and each of these starts with a deepening component, which is overlain by a maximum flooding surface/condensed section, followed by a shallowing component. Within the investigated database, seven rock textures are identified. Based on their grain size and whether they are mud- or grain-supported, they are grouped into three categories: 1) muddy textures; 2) packstone textures; 3) grainy textures. The statistical analysis has unravelled the diagenetic processes that have the biggest impact on reservoir-quality in the investigated oilfield, which include cementation by syntaxial calcite overgrowths and dolomitization. The models and the statistical analysis suggest that the best reservoirs are encountered in the central part of the investigated oilfield (i.e. shoal/outer shoal facies), where grain-supported limestone textures with syntaxial calcite overgrowth cement are common. These overgrowths have helped preserving depositional intergranular porosity and permeability during mechanical and chemical compaction. The results further reveal that the central part of the oilfield is more heterogeneous in terms of porosity and permeability distribution, compared to the northern and southern parts. A detailed description and quantification of both rock textures and diagenetic processes are necessary inputs for a valid geostatistical modeling of the reservoir properties, as diagenesis may modify the distribution of reservoir properties considerably only based on a rock texture simulation.