Innovative Integration of Geological Concepts in Dynamic Model History Matching for a Complex Offshore Carbonate Reservoir in Abu Dhabi, UAE

Abstract This study seeks to improve predictive accuracy in dynamic reservoir modeling by integrating geological concepts with historical field data. The primary focus is on enhancing horizontal permeability to achieve better alignment with production history. A comprehensive approach was employed, combining geological analysis with detailed data examination. Core samples and thin sections from 48 wells were meticulously studied to identify and classify key geological features, such as dissolution vugs, based on their impact on fluid flow. These features were correlated with reservoir properties like rock type and porosity to understand their influence on permeability. Additionally, MDT data was also analyzed from 20 key wells to assess vertical connectivity, revealing insights into flow barriers and conduits. The analysis yielded geologically robust permeability models that closely align with historical dynamic data, offering a significant advancement in reservoir characterization. Through meticulous examination of geological features, particularly vuggy rock types, the study uncovered substantial discrepancies between matrix permeability and well test permeability. These differences stem from the contrasting measurement scales employed in various assessments, as well as the static model's failure to account for critical geological features in the reservoir such as dissolution vugs, which play a crucial role in fluid flow dynamics. The research identified that certain rock types, especially those with vuggy textures, exhibited enhanced permeability that was not adequately captured in the static models. This omission often led to an underestimation of fluid flow potential, impacting the accuracy of reservoir simulations. The findings underscore the necessity for a more integrated and geologically informed approach to reservoir modeling, advocating for the inclusion of detailed geological observations to improve the predictive capability of dynamic models. This study presents an innovative approach for incorporating geological concepts into reservoir modeling, with a focus on the seamless interpolation of static and dynamic data to enhance History Matching and prediction accuracy. By integrating detailed geological features, the study offers critical insights that can lead to more effective reservoir management and optimized recovery strategies, ultimately improving efficiency and sustainability in the energy industry.