Plant Integrity Assurance by the Development and Deployment of Advanced NDE and Digitalization

In the Gulf of Thailand, PTT Exploration and Production are operating 231 platforms. And with facility ages up to 40 years, inspection programs are required to be more rigorous. Conventional inspection concepts, mainly requiring human direct assessment and data manipulation, are labor-intensive and requires facility shutdown for safe access. Therefore, company have been developing and deploying advanced NDE and digitalization to assure integrity with optimum inspection strategies, while keeping operational cost reasonable and avoiding work backlogs. The initiatives of advanced NDE (Non-Destructive Examination) and digitalization started in 2016, throughout the process of technical survey, feasibility study, proof-of-concept testing and field testing. Specific tools, parameters, demonstration pieces, procedures and interpretation have been chosen, analyzed and developed for specific inspection tasks for acceptable sensitivity and accuracy of NDE. At the same time, under the concept of total inspection and integrity management, company have implemented digitalization. The digitalization has been developed to supplement, aid and even replace conventional inspection data manipulation methods, which are based mainly on personnel. In this paper, sample cases of the applications of LRUT (Long Range Ultrasonic Testing) to detect and monitor corrosion under riser clamps, PAUT (Phase Arrayed Ultrasonic Testing) to monitor thermal fatigue cracking of vessels, and home-made Drones to monitor flares (while operating) and inspect tank internals are discussed. It has been found that, with proven, specific tool parameters and procedures, target damages and defects can be identified and monitored. 62% reduction in downtime per year required for safe access and assessment are attained. From the sample cases, cost saving at 17.83MMUSD per year is realized. Also, sample cases of digitalization are discussed. The paper describes cases of ML (Machine Learning) for image processing to detect and identify cracking, for characterization and prediction of metal loss. cases of RPA (Robot Processing Automation) for manipulating inspection results are described too. It has been found that ML provides 80% improvement in terms of accuracy and of interpretation time. RPA 71% reduces the time of manipulating inspection/NDE data, anomalies and metal loss calculation, apart from eliminating human errors. Finally, integrity management platform 21% saves direct inspection cost, by improving inspection strategies. As on-stream inspection concept is more important for increasing numbers of aging Oil and Gas facilities, advanced NDE methods play more vital roles. And with increasingly powerful computer-processing, digitalization is proven to provide higher accuracy and efficiency, with minimal errors. Concepts and sample cases explained in this paper reinforce these ideas with realized benefits of both cost saving and integrity assurance.