From Challenge to Opportunity: Detecting Incursions for Smart Well Interventions

Abstract Managing well performance efficiently requires integrating multiple data sources and ensuring proactive decision-making. This study presents an automated approach for smart well interventions, enabling operators to optimize production while mitigating sand influx risks. Interactive dashboards provide real-time insights into production trends, well conditions, and intervention planning, allowing field teams to respond swiftly to performance issues. By leveraging data-driven workflows, this solution enhances operational efficiency, reduces costs, and improves production outcomes. The operating philosophy consists of four components: 1D geomechanical analysis, sand ingression analysis, wellbore modeling and automated calibration, and automated minimum THP estimation. A 1D Mechanical Earth Model (1D MEM) calibrated with drilling events and caliper data was used as an input to the sand prediction model. The sand prediction model evaluates critical drawdown pressure (CDDP) and establishes a sand-free envelope. A calibrated digital twin is created using well test parameters. The automated sand mitigation workflow uses CDDP values and well models. The minimum flowing bottomhole pressure estimated from CDDP is translated into minimum THP for regular monitoring and sand control by the production team. The solution has three key layers: Data Integration: Enterprise tools, and real-time platforms, are connected to a central repository, enabling smooth data access across teams.Processing: Automated workflows power: Well Intervention Opportunity Management (IOM): A decision-support system that screens and ranks wells by constraints like sanding, economic potential, and intervention opportunities for rapid prioritization.Sand Influx Mitigation: A workflow that utilizes geomechanical modelling to define minimum tubing head pressure needed to prevent sand production, reducing sand-related failures and workovers.Visualization: A collaborative dashboard offers asset overviews, flags underperforming wells, and supports intervention planning through intuitive decision-support tools and performance monitoring. Implementing these automated workflows significantly enhances well management by enabling faster, more informed intervention planning. The IOM system streamlines well selection, allowing engineers to focus on high-impact opportunities, while the sand influx mitigation solution ensures stable operation by maintaining safe drawdown limits. Additionally, production monitoring dashboards offer a high-level view of field health, enabling faster detection of potential bottlenecks and underperforming wells before issues escalate. Overall, this integrated approach enhances production efficiency, supports proactive decision-making, and minimizes downtime. This solution bridges traditional petroleum engineering principles with modern data analytics to create a more scalable approach to well optimization and sand management. The integration of real-time data and automated workflows facilitates quicker decision-making and enhances collaboration across teams. Future developments will focus on refining intervention prioritization models and expanding predictive capabilities to further optimize field operations.