Updating the Post-Drilling Static Model Using AI-Based RRT and Tilted Paleo FWL to Enhance Drilling Strategy for the Marginal Field - Integrated Case Study from Onshore UAE

This paper emphasizes the importance of incorporation of newly drilled well data (reservoir properties and production results) for the well placement and field development planning optimization in complex carbonate reservoirs with tilted FWL and presence of paleo oil. The novel workflow has been proposed to update the latest static model that reconciles with post-drilling results through: AI-based rock typing incorporating pore structure parameters, Microporosity-adapted Archie saturation modeling with variable m, and Innovative FWL initialization specifically tailored to tilted reservoirs. The suggested workflow progresses from petrophysical reevaluation to drilling strategy optimization, ensuring model calibration with actual well results via integration of the following interpretation techniques: 1. AI-Driven Petrophysical Grouping (Machine learning clustering using 12 parameters including pore throat size distribution and micropore volume and Geological facies-constrained classification) 2. Enhanced Saturation Modeling (Dynamic Archie m exponent correlated with microporosity volume and Core-calibrated tortuosity adjustments) 3. Advanced FWL and Transition zone Characterization (Empirical paleo FWL surface replacing manual PC correction maps and Apparent FWL concept for 3D SHF initialization). The recalibrated petrophysical model became capable of revealing the source of the latest geological model misalignment with the actual newly drilled well data (predominantly horizontal wells). In such a way, the RRT update in conjunction with rock-based SHF improved the match between Archie saturation and calculated water saturation not only at well locations but also helped to characterize it in 3D space, offering a robust explanation for the dynamic behavior observed on the flanks of the field. Methodology of FWL initialization has changed from manually drawn Pc correction map to empirically derived function-based two-dimensional surface of Paleo FWL, well correlated with Shuaiba top structure. Thus, transition zone and flank areas got better precision and became characterized with higher degree of detail, leading to a perfect match in properties with recently drilled vertical and horizontal wells. Finally, the updated static model has resolved pre-existing uncertainties in water saturation and FWL position, thereby enhancing field understanding, increasing the accuracy of volume calculations, and providing opportunities for improved well placement and potential additional wells to optimize the field development plan. This study proposes the employment of a comprehensive workflow for static modelling of water saturation specifically designed for tilted carbonate reservoir with the variable paleo FWL, helping to revise the geological setting of the field, with further possibility of review and optimization of the field development strategy. This integrated approach highlights the importance of a revision of the input data, such as petrophysical models for rock typing / facies modelling and interpretation methodologies for tilted FWL and SHF initialization. Accurate transfer of petrophysical interpretation into static model properties ensures calibration with real well data and therefore enables model usability for well planning and any other operational activities. Subjects: Geological modelling, formation evaluation, reservoir simulation, reservoir characterization, field development planning