Addressing Non-Uniqueness in Guided Wave Tomography for Limited-View Corrosion Mapping

Guided wave tomography has proven to be an effective method for detecting pipeline corrosion, providing both location and quantitive estimates of wall thickness loss. However, the limited view geometry of source–receiver pairs on pipes leads to a significantly ill-posed problem. In practical terms, this means that the wall thickness measurements become unreliable, as small errors or noise in the data can result in large inaccuracies in the reconstructed thickness profile. To address the non-uniqueness inherent in Full Waveform Inversion (FWI) for guided wave tomography, we explore a joint inversion framework that combines multiple guided wave modes: specifically $A_0$, $S_0$, and $S{H}_1$. These modes have different sensitivities to wall thickness variations in pipelines, and by jointly inverting them, we aim to enhance the overall information content available to the inversion process. By deriving statistical measures of solution precision and accuracy through sampling-based analysis, we quantify the reliability of inversion outcomes under different mode-frequency configurations. These measures offer practical guidance for selecting suitable combinations in future experiments, helping to mitigate non-uniqueness without altering the sensor layout. This insight supports more informed system design choices for corrosion monitoring applications.