1. Getting More From Your Intelligent Pig Inspectionby
Roland Palmer-Jones, Prof. Phil Hopkins, and Andre Goncalves
Penspen Integrity
PPSA Seminar
Aberdeen
14 – Nov 2007

2. The Problem
Intelligent pigs are widely used
Large quantities of data are collected
Defects are generally reported in a simple spreadsheet format.
Simple clustering and defect sizing leads to safe conservative assessments

3. Inspection Technology
Outline
Inspection Technology
MFL UT
Defect Sizing
Defect Assessment
‘Complex Shape’ Assessment
Case Study

4. MFL Inspection
N MAGNET S
Flux Lines
Pipe Wall
© Penspen Ltd.

5. Relative measurement Depth MFL Defect Sizing Signal amplitude
Number of sensors affected
N MAGNET S
Flux Lines
Pipe Wall

6. MFL Data
© Penspen Ltd.

7. UT Inspection

8. Absolute Depth/Wall Thickness
UT Defect Sizing
Absolute Depth/Wall Thickness
Time difference between echo signals

9. UT Data
© Penspen Ltd.

10. Individual Defects
© Penspen Ltd.
© Penspen Ltd.

11. Multiple Defects?
© Penspen Ltd.

12. © Penspen Ltd.

13. Clustering
© Penspen Ltd.

15. Cluster

16. Evaluation Based on ‘Actual’ Shape
RSTRENG – Riverbottom Profile
DNV RP-F101 Complex Shape Method

17. RSTRENG

18. DNV RP-F101

19. Example 1

20. UT data
© Penspen Ltd.

21. Rectangular Profile Failure Pressure 219 bar

22. Riverbottom Profile Failure Pressure 305 bar

23. Example 2

24. Inspection/Repair Can be Expensive
© Penspen Ltd.
© Penspen Ltd.

25. Summary
Defect profile data gives assessment benefits
Profile data is collected anyway and so should be supplied in an accessible format with the inspection report.