Pipeline integrity management: Internal corrosion detection of oil and gas pipelines using fiber optics

Abstract

Oil pipelines are monitored for corrosion on regular intervals using conventional tools. A real-time monitoring solution was developed to avoid spontaneous failures that may occur between inspection intervals using distributed fiber optic sensors which are intrinsically safe. The fiber consists of a silica core and a polymer cladding coated with a metal layer from the pipeline's construction which upon corrosion exposes it to hydrocarbons altering its refractive index. Intensity of a traveling pulse drops and is captured by reflectometry techniques. The system was simulated and a laboratory scale setup is being developed to validate the model and test the solution. Alternatively, a strain based corrosion sensor for the detection of external and internal corrosion of pre-stressed and pressurized structures was developed and tested on mild steel samples readily available. Theoretically, a beam shaped sample under a displacement load exhibits a linear relationship between the strain observed at any point and the thickness of the beam cross-section. This property was exploited to detect thickness changes in pre-stressed mild steel samples in double bending under an electrochemically excited corrosion reaction. The corrosion reaction was excited by supplying a DC current to the cell in which the samples act as the anode of the system while graphite rods serve as the cathodes. A salt water electrolyte was used to complete the electrochemical cell while the strain was logged using Fiber optic Bragg Grating technology and conventional electrical strain gages simultaneously. The results showed a strong relationship between the corrosion rate observed by back calculation from supplied current and the time derivative of the measured strain values. This sensor can therefore be extended to a variety of structures under mechanical loading proving both valuable for its ability to measure corrosion rate in real time while maintaining an intrinsically safe nature appropriate by oilfield standards.

Date of Award	2015
Original language	American English
Supervisor	Nader Vahdati (Supervisor)