Carbonate rocks are usually very good carbonate reservoirs and can host giant fields, such as the Ghawar, Karachaganak or Lula fields. They can form in various depositional environments, stratigraphic and structural settings, and can be affected by many different diagenetic processes. As a result, they present very heterogeneous petroacoustic characteristics and are difficult to image and interpret even using up-to-date seismic data. Exploration and development of such reservoirs require to develop novel integrative approaches to better understand the regional-to-local sedimentological and diagenetic processes, which have shaped these reservoirs. The challenge of our study was to develop and run a fast and accurate workflow combining seismic interpretation, detailed sedimentological and diagenetic studies of wireline logs and core data, with deterministic stratigraphic forward and synthetic seismic modelling of a carbonate reservoir (average thickness of about 200 m) at an appraisal scale (650 km2, using a grid point spacing of about 200 to 500 m). A review of borehole and seismic data, and in particular lithofacies classification (facies type and facies group) and EOD definition (Environments Of Deposition), allowed us to define stratigraphic parameters such as accommodation space, carbonate production rates, sediment transport parameters, dissolution-cementation rates, … A series of numerical simulations were performed using the DionisosFlow stratigraphic model to simulate sedimentological and diagenetic processes through geological time. The simulation results were compared to the wireline and seismic data using the "stratigraphic model to seismic data" prototype until reaching a reasonable match between simulated and interpreted sediment proportions inside each flow unit. Finally, sensitivity analysis was performed. This stratigraphic forward and seismic modelling approaches made it possible to better understand the impact of sedimentary and diagenetic processes on large-scale carbonate reservoir properties and finally to reduce uncertainties on the appraisal-scale reservoir characterization.

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