The Bayesian methodology is employed to calibrate the accuracy of high-resolution ILI tools for sizing metal-loss corrosion defects on pipelines by comparing the field-measured depths and ILI-reported depths for a set of static defects, i.e. defects that are recoated and ceased growing. The measurement error associated with the field-measuring tool is found to be negligibly small; therefore, the field-measured depth is assumed to equal the actual depth of the defect. The depth of a corrosion defect reported by an ILI tool is assumed to be a linear function of the corresponding field-measured depth subjected to a random scattering error. The probabilistic characteristics of the intercept and slope in the linear function, i.e. the constant and non-constant biases of the measurement error, as well as the standard deviation of the random scattering error are then quantified using the Bayesian methodology. The proposed methodology is able to calibrate the accuracies of multiple ILI tools simultaneously and quantify the potential correlations between the accuracies of different ILI tools. The methodology is illustrated using real ILI and field measurement data obtained on two pipelines currently in service.

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