Pipeline Ultrasonic Thickness Data Analysis Using Gaussian Distribution

Introduction

It is crucial to determine the overall mechanical integrity of our pipelines. To achieve this, screening examination and inspection techniques such as guided wave ultrasonics or intelligent pigging systems have often been utilized. But those techniques can have some limitations and are often supplemented with visual examinations, as well as conventional spot UT thickness measurements (typically using an A-scan UT instrument). Of course, all of the data generated during these examinations must be compiled and properly analyzed. The mechanical integrity evaluation of an entire field, with a large number of pipelines, can require significant amounts of resources (i.e., time, economic, expertise) and can generate large volumes of data to be analyzed. API 570 (fourth edition, paragraph 7.1.3) allows the use of statistical analysis methods to establish a representative corrosion rate, remaining life estimate and/or re-inspection date of piping systems ^[1].

This article will discuss a statistical analysis method that was developed to evaluate the integrity of pipelines that can identify, in a first phase inspection, whether the nature of the active damage mechanism(s) are uniform (general) or localized. It can also help to identify the most indicative areas, which helps us develop a better inspection plan going forward and determine if more advanced (phase 2) inspections are needed. The analysis method is based on the application of a Gaussian distribution, which most correctly applies to the type of statistical population that is generated with the application of the non-destructive ultrasonic test (UT) A-scan. The result is a Gaussian bell graph presentation where the parameterization of the ideal pipe conditions is superimposed onto the actual data, thereby clearly showing the deviation of the actual data from the ideal condition.

Development of the Statistical Method

The proper interpretation of the results obtained through the application of the non-destructive evaluation (NDE) UT A-scan are subjective and reliant on the inspector's experience. Usually low, medium, and high readings are obtained, with respect to the nominal thickness of the pipe. In view of the data volumes and diversity, the use of descriptive statistics was considered, specifically the applicability of a Gaussian distribution, since through this it was possible to represent the behavior of the values of certain variables. In this case, the thickness variations can be influenced by random phenomena, such as corrosion that is caused by various damage mechanisms.