Method for operating dual controller
US-2017371310-A1 · Dec 28, 2017 · US
US9964967B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9964967-B2 |
| Application number | US-201313774561-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 22, 2013 |
| Priority date | Feb 28, 2012 |
| Publication date | May 8, 2018 |
| Grant date | May 8, 2018 |
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A method for monitoring a control of a parameter of one or more devices or systems in an oil or gas production site includes receiving process data, the process data being a result of the control of the parameter of the one or more devices or systems in the production site; smoothing the process data using a polynomial filter while preserving features of the process data to obtain smoothed data; and applying a pattern recognition algorithm to the smoothed data to determine whether there is a malfunction condition in the one or more devices or systems.
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What is claimed is: 1. A method of controlling a device in a hydrocarbon production site comprising: operating a plurality of physical devices or systems in the hydrocarbon production site; receiving, by a computer system, representative benchmark process data from the plurality of physical devices or systems in the hydrocarbon production site for a period of time of normal operation, wherein each physical device or system includes at least one valve, and wherein each valve is controlled by a controller system using one or more loops, and wherein the representative benchmark process data is selected from the group consisting of temperature, pressure, fluid flow rate, operation of a valve, and any combination thereof; receiving, by the computer system, real-time process data from the plurality of physical devices or systems outside the period of time of said normal operation, the real-time process data being selected from the group consisting of real-time measured temperature, pressure, fluid flow rate, operation of the valve, and any combination thereof; applying, by the computer system, a data-driven covariance benchmark algorithm to the real-time process data and the benchmark process data corresponding to the one or more loops to determine whether the real-time process data from the plurality of devices deviates from the benchmark process data from the plurality of devices; in response to determining that the real-time process data deviates from the benchmark process data indicating a degraded one or more loops in the one or more loops, applying, by the computer system, an angle-based contribution algorithm to determine which one or more loops in the one or more loops are degraded, wherein a degraded one or more loops in the one or more loops is indicative of a deteriorating condition of one or more controllers controlling one or more physical devices or systems or a deteriorating condition of the one or more physical devices, or both; applying, by the computer system, a Savitzky-Golay smoothing filter to the real-time process data for each degraded control loop of the one or more degraded loops while preserving features of the real-time process data corresponding to the degraded one or more loops to obtain smoothed data; applying, by the computer system, a pattern recognition algorithm to the smoothed data to determine whether a valve stiction condition exists in a valve corresponding to each degraded control loop, wherein the pattern recognition algorithm comprises a curve fitting method, wherein the curve fitting method further comprises calculating a sinusoidal fitting, calculating a sawtooth fitting, and calculating a stiction index based on the sinusoidal fitting and the sawtooth fitting and based on a value of the calculated stiction index determining that the valve stiction condition exists in the valve corresponding to each degraded control loop; and in response to determining that the valve stiction condition exists in the valve corresponding to each degraded control loop using the pattern recognition algorithm, taking corrective action to resolve the valve stiction. 2. The method according to claim 1 , wherein if the stiction index is smaller than a threshold value it is determined that there is substantially no stiction of the valve, and if the stiction index is greater than the threshold value, it is determined that there is stiction in the valve. 3. The method according to claim 1 , wherein applying, by the computer system, the Savitzky-Golay smoothing filter comprises filtering the degraded real-time process data while preserving features of the degraded real-time process data, the features being selected from the group consisting of maxima in the degraded real-time process data, minima in the degraded real-time process data, width in oscillation within the degraded real-time process data, and any combination thereof. 4. The method according to claim 1 , wherein using the Savitzky-Golay smoothing filter comprises selecting a smoothing window depending on a period of oscillation in the degraded real-time process data. 5. The method as in claim 1 , wherein calculating the stiction index comprises comparing a mean square error of the sinusoidal fitting and the sawtooth fitting. 6. The method as in claim 5 , wherein the comparing comprises evaluating S I = MSE sin MSE sin + MSE tri , where MSEsin is the mean square error of the sinusoidal fitting and MSEtri is the mean square error of the sawtooth fitting, and SI is the calculated stiction index. 7. A non-transitory computer readable medium encoded with computer executable instructions for performing the method of claim 1 . 8. The method according to claim 1 , wherein at least one of the devices or systems is offshore. 9. The method according to claim 1 , further comprising determining valve stiction in at least one degraded control loop that is a multi-loop. 10. The method according to claim 1 , further comprising determining valve stiction in at least one degraded control loop that is a single loop. 11. A computer system for controlling a device in a hydrocarbon production site comprising: a storage device storing executable instructions for performing a method; and a processor in communication with the storage device, the processor being configured to execute the instructions to cause the computer system to: receive representative benchmark process data for a plurality of physical devices or systems in the hydrocarbon production site for a period of time of normal operation, wherein each physical device or system includes at least one valve, and wherein each valve is controlled by a controller system using one or more loops, and wherein the representative benchmark process data is selected from the group consisting of temperature, pressure, fluid flow rate, operation of a valve, and any combination thereof; receive real-time process data for the plurality of physical devices or systems outside the period of time of said normal operation, the real-time process data being selected from the group consisting of real-time measured temperature, pressure, fluid flow rate, operation of the valve, and any combination thereof; apply a data-driven covariance benchmark algorithm to the real-time process data and the benchmark process data corresponding to the one or more loops to determine whether the real-time process data from the plurality of devices deviates from the benchmark process data from the plurality of devices; in response to determining that the real-time process data deviates from the benchmark process data indicating a degraded one or more loops in the one or more loops, apply an angle-based contribution algorithm to determine which one or more loops in the one or more loops are degraded, wherein a degraded one or more loops in the one or more loops is indicative of a deteriorating condition of one or more controllers controlling one or more physical devices or systems or a deteriorating condition of the one or more physical devices,
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