Guided wave monitoring of pipelines

Abstract

Guided wave sensors are commonly used in the oil and gas industry to inspect pipework for damage. Early sensor were detachable and designed for single inspections, but current best practice is to permanently attach sensors and take repeat readings. Known as a monitoring configuration, this approach offers potential benefits in terms of cost, defect detection capability and safety. There are however implementation challenges that are still to be resolved, particularly the need to compensate collected data for changes in environmental and operational conditions. The interaction of guided waves with general corrosion is also poorly understood. This thesis seeks to address both issues, beginning with a finite element study of the interaction of guided waves with rough surfaces. These rough surfaces are a basic model for general corrosion and this study shows that attenuation seen in commercial inspections can be explained by significant scattering of waves by the rough surface. This scattering is shown to be a function of the rough surface characteristics, pipe diameter and inspection wave frequency. This study was computationally expensive and made possible by recently developed simulation tools, particularly graphics processing unit based solvers. The development and construction of these simulation tools is described in detail. The second major theme of this thesis is improved signal processing for monitoring data based on Independent Component Analysis [ICA]. ICA was applied to numerous example signals and found to correctly separate structural anomalies from surrounding noise. This technique was then compared to best practice techniques from industry (residual processing and singular value decomposition [SVD]) and it was found that SVD and ICA performed much better than residual processing under a range of conditions. In general ICA performed better than SVD, but was less robust to outlier behavior. The framework used for this comparison is itself novel and is described.