Diagenesis in carbonate successions has a significant impact on reservoir characteristics. The Quantitively Diagenetic Modeling (QDM) approach, introduced in this study, was conducted based on the micro-to macro- scale data integration within the Cenomanian-early Turonian Sarvak carbonate rocks deposited in the Abadan plain. The adopted approach is based on an integrated analysis of petrographical data interpretation, well logs evaluation and seismic attribute analysis. The sedimentological and diagenetic studies were investigated based on the petrographic descriptions coupled with the analysis of well logs and seismic data. Seven facie associations corresponding to five depositional settings were identified. Among these, the main diagenetic processes including cementation and dissolution were distinguished as the primary diagenetic process affecting the Sarvak reservoir properties. The primary petrographical diagenetic process were classified based on the analysis of well log response and seismic amplitude refraction using the Artificial Neural Network (ANN) approach. In this context, the diagenetic zonations were concluded, reflecting geological features (facies and depositional setting), the reservoir characteristics (porosity, permeability), and seismic reflection (acoustic impedance and seismic reflectivity). The identified classes include mud-dominated facies with low microporosity/cemented micropores (DG-0), microporous cemented grainstone/packstone (DG-1), mud dominated facies with vugs and microfractures (DG-2), grain dominated facies with vuggy pores (DG-3), and dissolved rudist biostrome (DG-4). The proposed diagenetic classes introduced in this study propagated based on the TGS algorithm by using a new workflow to capture the variation of each diagenetic class throughout the studied fields. In this study, a new workflow was proposed based on the quantitative approaches at multiscale to reduce the uncertainty of property modeling within the studied carbonate reservoir considering the diagenetic overprints. The adopted approach implies that using the integrated data at multi scales (well to seismic) has a significant role in understanding the diagenetic pathways and its effects on the reservoir characteristics.

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