Input-Output Cross Autocorrelation Diagram (IO-CAD) for control loop performance assessment in offshore oil production

Abstract

Severe slugging is a prevalent issue in offshore oil wells that significantly hampers oil production. While active pressure control has proven effective in mitigating this problem, determining optimal setpoints remains a manual and labor-intensive procedure. This study introduces the Input-Output Cross Autocorrelation Diagram (IO-CAD), which examines both input and output autocorrelations to provide a more comprehensive assessment of control loops compared to previous methods that only use output autocorrelation data. Four indicators based on IO-CAD were developed and tested in two case studies involving offshore oil production. They were compared to an oscillation detection method published in the literature, as oscillations in the control loop may indicate the slugging flow. Early detection of slugging patterns is crucial in offshore oil production to prevent severe slugging and stabilize control loops. The results demonstrated that the IO-CAD indicators are robust against setpoint changes, disturbances, and noise in the control loop performance assessment, while the oscillation detection method from the literature is sensitive to measurement and process noise, as well as control loop oscillations.