New Modification Method for Safety Factor of ASME Considering Pipeline Big Data

Abstract

Due to the potential severity of oil and gas pipeline accidents, the accurate assessment of defective pipelines is a critical focus in petroleum engineering. Some parameters in the assessment standards are, however, limited in their technologies. This essay provides a new modification method for the safety factor (SF) of the widely accepted ASME Manual for Determining the Remaining Strength of Corroded Pipelines (B31G-2012). In the provided method, the SF is modified considering critical factors based on pipeline big data, using two big data analysis techniques, namely, correlation analysis and the analytic hierarchy process (AHP), to improve the previous one in which only the pressure of the pipeline was used during calculation. In this paper, data from an in-service pipeline is manipulated as a case to show how the modified SF is calculated. Comparative analysis with the previous results provides clear evidence that the new results are more accurate and that the SF changes according to different risk levels.