Abstract
Despite the spectacular advances in seismic and log acquisition and interpretation, and in 3D and 4D modeling, the risks involved in the exploration of new, deeper, depositional, tectonic or diagenetically-complex prospects remain large. This happens essentially because these sophisticated methods simply lack information on an essential part of petroleum systems: the reservoir. Most new prospects represent clastic or carbonate rocks with strong diagenesis. For these, the conventional, indirect evidence of texture and composition provided by logs and conventional, simplified petrographic descriptions is simply not enough. There is an emerging trend for the integration of systematic petrographic analysis, aided by petrologic and geochemical analyses, with log analysis, petrophysics, and seismics, to tackle the challenges represented by such reservoirs. Petroledge, an intelligent database system combining resources from relational databases and knowledge-based expert systems, was created to support systematic analysis, storage and processing of detailed petrographic information on primary structures, textures and constituents, and mostly on the habits, location and paragenetic relations of diagenetic constituents and pore types. Such systematically-organized petrographic information can be effectively retrieved and integrated into 3D reservoir models and flow simulation softwares. Systematic petrographic characterization can be used to calibrate log and seismic attributes through reservoir petrofacies, defined by the combination of key petrographic parameters. Log and seismic facies and seismic reflectors calibrated by such reservoir petrofacies allow the realistic 2D and 3D representation of reservoir quality and heterogeneity, leading to enhanced static and flow simulations during development and production, and increasing the precision and efficiency of seismic interpretation in deep, new or unconventional settings. The appropriation of systematic petrographic characterization into realistic reservoir quality models will allow a better assessment of exploration risks and optimized production procedures. The challenges involved in the exploration and production of complex reservoirs will be surpassed with the intelligent integration of petrography into the operational E&P workflow.
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