Digitalizing Reservoir Surveillance Through Real-Time Workflows for Optimized Field Performance and Reduced Testing Costs in Water-Flood Reservoirs Using a Digital Oilfield System

Abstract The transition from conventional reservoir surveillance to a digitized approach is achieved through the implementation of a real-time monitoring system that enhances field and well performance. Traditionally, field surveillance relied on periodic physical well tests and manual monitoring, which may lead to challenges with decision making and managing reservoir behavior. The introduction of the digitized real-time system has revolutionized this process by continuously tracking pro- duction dynamics and reservoir conditions. The system supports timely decision-making during the primary depletion and development phases, providing accurate measurement for reservoir pressure, production rates, and water injection impacts. The system integrates calibrated physical models of the reservoir, wells, and surface network. It automates well rate and condition diagnostics using real-time pressure and temperature data, delivering continuous estimates of reservoir pressure, productivity index (PI), water cut (WC), and pump wear. The approach enables automated well rate calculations without the need for frequent physical well tests. The data is used to identify optimization opportunities such as ESP adjustments, choke setting modifications, pipeline routing, and debottlenecking studies. A revised testing strategy was also introduced, shifting from frequent physical tests to a 45-day or bi-monthly interval, depending on well performance stability. Implementation of the real-time system has significantly improved field performance and reservoir management. The ability to continuously monitor well production and reservoir pressure has provided more accurate well allocation factors and reduced reliance on physical well tests, resulting in annual cost savings. Short- and long-term optimizations have been achieved, including enhancements in ESP operations, choke settings, and infrastructure utilization. The system has improved performance assessment by providing daily inferred validation of potential and has enabled better evaluation of water injection strategies. It is now being expanded to monitor injection wells, improving injection efficiency and identifying communication with producer wells. Overall, digitalizing reservoir surveillance delivers deeper insights into well and reservoir behavior and supports improved recovery strategies. This paper introduces a novel real-time monitoring approach that digitizes reservoir surveillance by combining auto- mated rate estimation and integrated physical modeling, reducing the need for frequent testing while improving production performance and reservoir insight.