Analytical Modeling Tool for Design of Hydrocarbon Sensitive Optical Fibers.

Pipelines are the main transportation means for oil and gas products across large distances. Due to the severe conditions they operate in, they are regularly inspected using conventional Pipeline Inspection Gages (PIGs) for corrosion damage. The motivation for researching a real-time distributed monitoring solution arose to mitigate costs and provide a proactive indication of potential failures. Fiber optic sensors with polymer claddings provide a means of detecting contact with hydrocarbons. By coating the fibers with a layer of metal similar in composition to that of the parent pipeline, corrosion of this coating may be detected when the polymer cladding underneath is exposed to the surrounding hydrocarbons contained within the pipeline. A Refractive Index (RI) change occurs in the polymer cladding causing a loss in intensity of a traveling light pulse due to a reduction in the fiber's modal capacity. Intensity losses may be detected using Optical Time Domain Reflectometry (OTDR) while pinpointing the spatial location of the contact via time delay calculations of the back-scattered pulses. This work presents a theoretical model for the above sensing solution to provide a design tool for the fiber optic cable in the context of hydrocarbon sensing following corrosion of an external metal coating. Results are verified against the experimental data published in the literature.

Corrosivity Sensor for Exposed Pipelines Based on Wireless Energy Transfer.

External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design.