Enhancing production monitoring: A back allocation methodology to estimate well flow rates and assist well test scheduling

Production flow rates are crucial to make operational decisions, monitor, manage, and optimize oil and gas fields. Flow rates also have a financial importance to correctly allocate production to fiscal purposes required by regulatory agencies or to allocate production in fields owned by multiple operators. Despite its significance, usually only the total field production is measured in real time, which requires an alternative way to estimate wells’ production. To address these challenges, this work presents a back allocation methodology that leverages real-time instrumentation, simulations, algorithms, and mathematical programming modeling to enhance well monitoring and assist in well test scheduling. The methodology comprises four modules: simulation, classification, error calculation, and optimization. These modules work together to characterize the flowline, wellbore, and reservoir, verify simulation outputs, minimize errors, and calculate flow rates while honoring the total platform flow rate. The well status generated through the classification module provides valuable information about the current condition of each well (i.e. if the well is deviating from the latest well test parameters), aiding in decision-making for well testing scheduling and prioritizing. The effectiveness of the methodology is demonstrated through its application to a representative offshore oil field with 14 producing wells and two years of daily production data. The results highlight the robustness of the methodology in properly classifying the wells and obtaining flow rates that honor the total platform flow rate. Furthermore, the methodology supports well test scheduling and provides reliable indicators for well conditions. By utilizing real-time data and advanced modeling techniques, this methodology enhances production monitoring and facilitates informed operational decision-making in the oil and gas industry.