Session: 03-02-01: Integrity and Performance of Welded Joints

Submission Number: 155604

Burst Pressure Prediction of Defective Pipeline Test Spools by Metal Magnetic Memory Method 

Accurate prediction of burst pressure is a critical factor in ensuring pipeline system safety and reliability, especially within industries such as oil and gas where failures can have severe consequences. Current practices in industrial pipeline inspection involves intelligent pigging systems, i.e. ultrasonic testing (UT), magnetic flux leakage (MFL), eddy current techniques etc., which are oriented toward detection of the geometry of defects. More accurate inspection capability is required to evaluate stress, in particular to detect stress concentration zones due to today’s heightened safety expectations in carbon steel pipelines. In recent years, the metal magnetic memory (MMM) method has emerged as a non-invasive and efficient alternative to enhance the predictive capabilities of these assessments. This paper presents a novel approach for predicting the burst pressure of defective pipelines using MMM, aiming to improve both safety and reliability in pipeline management.

In this study, defects of varying depths and lengths were introduced to API 5L X42 and ASTM A106 test spools (with diameters of 6 inches and 4 inches) through an electrolysis-based method. These defective test spools were subsequently subjected to pressurized burst testing, during which MMM signals were measured continuously on the surface of the test spools. Additional data collection was performed using pressure transducers and strain sensors to provide comprehensive insights into the stress and pressure distributions. The focus of the analysis was on the behavior and distribution of MMM signals, particularly around defect areas, under increasing internal pressure.

The results reveal a clear evolution of MMM signals corresponding to the rising internal pressure, indicating localized stress concentration at defect sites. From this data, a formula was derived for calculating the burst pressure of defective pipelines based on the magnetic stress concentration factor. This formula enables an accurate, predictive approach to assessing pipeline burst pressure, achieving a prediction error within 10% when compared to actual burst test data. This MMM-based prediction model also demonstrates significant advantages over traditional models, such as ASME B31G and DNV-RP-F101, which typically depend on defect geometry alone. The MMM method captures stress-induced magnetic changes, providing a more direct assessment of failure risk.

Presenting Author: Choong Meng Lam PETRONAS Carigali Sdn Bhd

Presenting Author Biography: Lam Choong Meng (Raymond) is a Principal Pipeline Integrity Engineer from PETRONAS Carigali. He is also an European Engineer, an UK Chartered Engineer, a Professional Engineer, and also a Professional Technologist with over twenty seven (27) years of professional experience, which include both Oil & Gas Client Operator and Consulting Development experience. Additionally, he is an International team player with deep international awareness gained through long term assignments and postings across Europe, Middle East and Asia.
He has presented and published more than 10 papers in reputed international conferences.
He is an experienced Pipeline Professional Engineer specialized in a range of fields including Carbon Capture & Storage (CCS), CO2 pipeline repurpose, safeguarding pipelines, rigid and flexible risers integrity, advance inspection technologies, Pipeline Integrity Management System (PIMS), operational and intelligent pigging, pipeline repair activities, pipeline mothballing and replacements, Fitness for Service (FFS) assessments, Risk Based Inspection (RBI) assessments, pipelines life extension studies, pipeline design review and pipeline leak detection system.