Control Performance Monitoring of Excessive Oscillations of an Offshore Production Facility

Abstract

In remote operation of offshore platforms, real time control systems must be well maintained for efficient and safe operations. Early detection of control and equipment performance degradation is critical and is the foundation for implementing higher level integrated optimization. Poor control performance is usually the result of undetected deterioration in control valves, inadequate performance monitoring, and poor tuning in the controllers. In this work, data-driven approaches to monitoring control performance are applied to an offshore platform. The minimum variance control benchmark for single loops and the covariance benchmark for multi-loops are used to detect deteriorated control variables. The covariance benchmark is used to determine the directions with significantly worse performance versus the benchmark. To detect valve stiction, the Savitzky-Golay smoothing filter is combined with a curve fitting method. The Savitzky-Golay filter has the advantage of preserving features of the distribution such as relative maxima, minima and widths. A stiction index is used to indicate whether a valve stiction occurred. The OSIsoft PI system is suggested as the implementation platform. Real-time data can be exchanged between PI and MATLAB via OPC interface.