This paper discusses a comparative system and method for inspecting a carbon steel pipeline utilizing the magnetic gradient tomography method (MTM-G) and intelligent pig (IP). The data and results from both technologies complementarily identify stress-related defects, their dimensional characterization, and orientation effectively. The studies analyze the data and results given by both systems post-inspection and are valuable in the further optimization of inspection and maintenance processes.

While MTM-G measures the mechanical stress directly through magnetic field gradient of the pipeline under in situ conditions, IP, on the other hand, provides the geometry and orientation location of the anomalies. In order to compare and complement the outputs, we established a baseline of fabricated defects with verified dimensions on the intended pipeline for inspection. Post-inspection, the reported results from both technologies are assessed and compared accordingly by the defect-matching process. Subsequently, we use a standard statistical analysis method to analyse the probability of identification (POI) and their dimensions for the comparative studies.

The MTM-G notably determines the comparative degree of danger of anomalies by a direct quantitative assessment of the mechanical stresses reflected from the distribution of magnetic field gradient along the pipeline. Therefore, with the additional data on the geometrical parameters of the defects, subsequent calculation or correlation can be established to assess the impact of anomalies on the overall pipelines' safe operation and their constituted imminent risks.

Based on the study, the POI of MTM-G can be confirmed and enhanced from the sizing information of the defects and their orientation location on the pipeline provided by the IP inspection technology. On the other hand, the defects' severity in terms of remaining wall thickness can be enhanced and complemented with MTM-G finding. As a result, the integrative studies may provide comprehensive findings that become the basis for improving Pipeline Integrity Management.