Session: 03-03-10 Feature Assessment Case Studies - Material Properties I

Paper Number: 133839

133839 - An Insight Into What it Takes to Validate Inline Inspection Tools for Reliable Hard Spot Identification and Measurement 

Abstract: 

A hard spot is a localized area of increased hardness, defined in 49 CFR (Code of Federal Regulations) Part 192 as "an area on steel pipe material with a hardness greater than or equal to Rockwell 35 HRC (Brinell 327 HB or Vickers 345 HV10)".  Hard spots result in localised areas of increased residual magnetic field following magnetisation by an inline inspection tool run. These residual fields can be measured using a low or no field approach and used to detect and classify hard spots and to predict the hardness.

 

There are significant challenges in moving from pull test or dig data to creating a validated specification for hard spot inspection. The essential variables for hard spot inspection - sources of variation which must be controlled within defined limits for a successful result - are more numerous than for comparable inline inspection technologies. This is due to the two-step magnetization and measurement process and the range of factors related to the pipeline conditions, the hard spots themselves, and the inspection tool which could affect the magnitude of the residual field. The relative scarcity of hard spot examples and the difficulty in manufacturing hard spots to predictable tolerances means that the data required to validate across the range of all essential variables is not readily available.

 

This paper describes how Baker Hughes, in collaboration with industry partners, are using a multi modal approach to combine FEA (Finite Element Analysis), pull test and dig data to evaluate the complex interaction of the essential variables that contribute to the challenging task of reliably identifying hard spots in the field. The authors will also discuss the outcomes of the detailed validation program that has successfully resulted in a robust Probability of Detection (POD), Probability of Identification (POI) and Probability of Sizing (POS) specification with the confidence the industry needs to establish cost effective mitigation programs.

Presenting Author: Steven Farnie Baker Hughes

Presenting Author Biography: Steve Farnie is Regional Data Science Manager based in Cramlington, UK. Steve has over 20 years’ experience in the pipeline industry and has held roles as Mathematician, Sizing Specialist, Software Developer, Software Team Leader and Data Scientist. Steve holds a BSc in Mathematics from the University of Warwick and an MSc in Mathematical Modelling from the University of Coventry, UK.

Authors:

Steven Farnie Baker Hughes
Anthony Tindall Baker Hughes