MINI-FALL OFF TESTS AS A COST-EFFECTIVE TOOL FOR RESERVOIR CHARACTERIZATION AND DST DECISION-MAKING IN DEEPWATER CONVENTIONAL RESERVOIRS

This research introduces a methodology employing Mini-Fall Off injection tests to enhance reservoir characterization and inform Drill Stem Testing (DST) decision-making in deepwater conventional reservoirs. The methodology begins with log-driven permeability estimation, which is corrected using mobility data from Wire Formation Tester (WFT) point results. Despite these corrections, uncertainties persisted regarding the dominant permeability, which is crucial for ensuring the minimum required deliverability for DST. To address these uncertainties and flow assurance challenges, the Mini-Fall Off injection test was employed to estimate permeability within the target flow zone unit of the conventional reservoir. This approach allowed for precise permeability assessment in specific zones, thereby enhancing the overall understanding of reservoir quality and well deliverability. The Mini-Fall Off test provided critical Value of Information (VOI) by revealing that the well deliverability did not meet the minimum required flow rates for DST, leading to the cancellation of DST and substantial cost savings. The application of Mini-Fall Off tests demonstrates a significant advancement in reservoir assessment strategies, offering a cost-effective and efficient alternative to traditional methods. By integrating log-driven permeability data with WFT-derived mobility data and employing the Mini-Fall Off test, the methodology provides a comprehensive framework for reducing uncertainties and optimizing resource allocation in the oil and gas industry. Furthermore, this technique underscores the importance of VOI in data acquisition and decision-making processes throughout the asset lifecycle, from exploration to development. The results of this study highlight the potential for Mini-Fall Off tests to become a standard practice in reservoir characterization, particularly in deepwater conventional reservoirs where cost and efficiency are paramount. This work presents a novel, cost-effective approach to obtaining accurate reservoir characterization, thereby demonstrating its potential to optimize operational efficiency and resource management in the oil and gas sector.