Reliability analysis of condition monitoring data on aging plants: A case study from topside static mechanical systems

The quality of static mechanical systems´ integrity control process on aging oil & gas production and process plants (P&PPs) depends on the accuracy of the condition monitoring data. This is especially the case since accurate interpretation of the data could significantly aid the right decision-making at the right time in the right location. However, anomalies have been observed in the historical inservice inspection data records pertaining to most aging plants under study. Such anomalies result in sub-optimal inspection decisions and jeopardize the quality of an inservice inspection program. The uncertainties of condition monitoring data have been discussed in the literature and industrial community over the years. A number of approaches have been proposed to address the various challenges pertaining to uncertainties present in the inservice inspection data. This manuscript suggests an empirical approach for quantifying the reliability of condition monitoring data to estimate the level of anomalies present in the in-service inspection data and to investigate the source of these anomalies. A case study has been carried out using three different P&PPs functioning on the Norwegian Continental Shelf. The flowline system of each plant has been selected as that has been given highest risk priority.