Slug Flow Monitoring in Pipes Using a Novel Non Intrusive Optical Infrared Sensing Technology

The application of real - time monitoring technologies presents a means to harnessing proactive or reactive controls in minimizing severity effects of slugging in the production system. This paper presents the development of a non-intrusive optical infrared sensing (NIOIRS) setup, for slug monitoring in pipes. The flow characteristics monitored were the development of slug flows and average phase fractions of gas and liquid in a vertical test section (0.018m by 1m) for superficial velocities of 0-0.131 m/s for water and 0 – 0.216 m/s for air. The measurement principle was based on the disparities in refractive indices of each phase in the sensing area. The sensing component of the sensor consisted of two pairs of IR emitters and photodiodes operated at wavelengths of 880 nm specifications. A circuit, for signal conditioning, amplification and data acquisition was set up to convert infrared light detected into voltage signals. Development of slug flow regimes was monitored from signal distributions binned under reference voltages. The transitions from bubble to slug flow, were observed at 10 percent count of the signal distributions around typical sensor response for air. Validation from photos showed good agreements with the sensor response. A single peaked distribution around the response for water indicated bubble flow regimes, with the development of two peaks indicated increasing gas slugs for increasing superficial gas velocities compared to liquid slug in the pipe. Phase fraction results were interpreted from a derived calibration models, which were based on the average observed response and reference responses of water and air over time. This model was compared with swell level changes, photographs and homogenous and drift flux correlation with agreement within maximum error bands +/- 0.5 % based on the swell level method and +/- 0.3% based on photographs. The Real-time application was carried out via the execution of an algorithm which incorporated the calibration information from the NIOIRS. The derived signals were processed and analyzed onto a display to identify slug flow development and phase fractions in real-time. A cheap and accurate sensing setup has been developed with the potential of real time monitoring of flow regimes and phase fraction determination.