1. In-Line Inspection & NDE for Pipe Properties
Lloyd Pirtle
Sr. Technical Representative
May 21st, 2015

2. Contents
Multiple Data Sets (MDS) ILI Tool Platform
Magnetic Characteristics
Grouping Pipe Joints (Creating Material Bins)
Positive Material Identification (NDE Process)
Conclusions

3. Multiple datasets (MDS)

4. Multiple Data Sets (MDS): Configuration
High Res Deformation
Low Field Magnetism
High Field Axial MFL
SpirALL® MFL Technology
Drive Section with Odometers

5. Value of Multiple Data Sets (MDS)
Axial metal loss
Long Seam
Selective Seam Corrosion
Seam anomalies
Seam variations
Volumetric Metal Loss
Mill Anomalies
Metal Loss in Girth Welds
Value of Multiple Data Sets (MDS)
Spatial Position of Pipeline
Bending Strains
Volumetric Anomalies
Internal/External Discrimination
Detect Mill Anomalies
Extra Metal
Detect Dents
MFL w/ IDOD
Axial grooving & slotting
Discriminate Planar vs Volumetric
XYZ
Accurate location of dig sites
SMFL
Spatial locations of features and anomalies
Pipe Type Properties
Gouging
Discriminate Mill Anomalies
Calculate Bending & Dent Strains
Bend Radii
Direction of Bends
DEF
LFM
Prediction of Hard Spot hardness
Gouging
Discriminate Mill Anomalies
Click through each circle in the Venn diagram, discussing the value of each individual technology first, then highlighting the value where there is overlap.
Dents w/ Metal Loss
Permeability Anomalies (i.e. Hard Spots)
Pipe Grade Changes
Mechanical Strain
Bore Changes
Measure Dents
Dents w/ Metal Loss
Re-rounding of Dents
Cycling of Dents
Dent w/ Residual Stress

6. Magnetic Characteristics

7. Magnetic Characteristics
Joints of steel pipelines can be identified by the following properties:
Manufacture – This is the first half of the pipe creation process where the molten steel ingot is formed into billets (seamless) or slabs (welded)
Milling – The forming of slabs or billets into pipe leave magnetic signatures and small bore differences that can be used for identification
Pipes with similar manufacturing and milling can be grouped together and should have similar material properties

8. Low Field MFL - Steel Microstructure
Thursday, February 9, 2012
Low Field MFL - Steel Microstructure
Weld
Low Carbon
Hard Spot
High Carbon
The examples here show how steel is different at the microstructure level; residual or low field MFL will detect any changes at this level. Discuss the differences at the microstructure level of a Weld, Low Carbon and High Carbon Steel; while on the surface – looking at joints of pipe as they appear in the ditch – different pipe looks the same. Also note that hard spots can lead to failure (the example in lower right hand corner). Again, this can simply be referred to as a “magnetic permeability map”. “Residual or low field creates a magnetic permeability map of the pipeline.”

9. Threat: Pipe Properties
All samples are 0.188” WT

10. Multiple Data Sets (MDS) For Pipe Properties
Long Seam
Seam variations
Accurate location of dig sites
MFL w/ IDOD
XYZ
SMFL
Pipe Type Properties
Spatial locations of features and anomalies
DEF
LFM
Discriminate Mill Anomalies
Click through each circle in the Venn diagram, discussing the value of each individual technology first, then highlighting the value where there is overlap.
Bore Changes
Mill signatures
Permeability Anomalies (i.e. Hard Spots)
Pipe Grade Changes

11. Creating bins

12. Creating Bins
Steel pipeline joints can be identified by the following properties. Manufacture – This is the first half of the pipe creation process where the molten steel ingot is formed into billets (seamless) or slabs (welded). Milling – The forming of slabs or billets into pipe leave magnetic signatures and small bore differences that can be used for identification. Pipe with similar manufacturing and milling can be grouped together and should have similar material properties (Pipe Joint Classification – PJC). PJC, combined with PMI (Pipe Identification), will help satisfy IVP requirements for gaps in material records.
Review the above bin differences in each dataset. Note LFM clearly distinguishes permeability differences related to manufacture and/or milling. SMFL reveals differences in seam weld signature between bin 1 and 2.

13. Threat: Pipe Properties
po id
type
dist begin
lat
long
pipe ys
pipe sf
pipe matl
pipe manuf
pipe mop T
Girth Weld
42000 1
ERW
X42
8690 T T T T T T T T T
35900 B
6720 T T T T T T T T T T T T
Sections of unidentified pipe can be matched to sections with records
Groups of unmatched joints can be tested using PMI
Pipe Joint Classification results example. Mention that sections of unidentified pipe can be aligned with pipe where records exist. Any joints not able to be matched during PJC process – and no material records exist – would then be candidates for PMI.

14. Positive material identification (PMI)

15. Positive Material Identification Process
TDW’s PMI process is a Validated process with established Accuracies and Tolerances
In lieu of destructive removal of coupon
In lieu of line shut-down
In lieu of Laboratory testing
Talk on our validation process up at Kiefner at the request of PHMSA

16. Specifications for PMI NDE Services
TDW’s PMI process is a Validated process with established Accuracies and Tolerances
No Pressure reduction requirements
Minimum exposed pipe = 3 ft.
In lieu of
destructive removal of coupon
of line shut-down
Laboratory testing

17. Specifications for PMI NDE Services
MPA temperature operating range 14°F to 115°F (-10°C to 46.1°C)
OES temperature operating range 32°F to 122F° (0°C to 50°C)
MPA maximum indention depth 0.006” (0.152mm)
OES maximum burn depth ” (0.033mm)
PLS1 pipe – All grades, all vintages. Grading per API5L-Tbl 4&6
PLS2 pipe – All grades, YS, TS, CA, & CE Properties

18. Mechanical Properties Assessment (MPA) for material Yield Strength & Tensile Strength

19. MPA Continued
The MPA indenter automatically adjusts and measures the load necessary to achieve a predetermined depth throughout the multiple sequential load/depth measurement processes.
Once the final load is applied at the individual location and the final maximum depth of 0.006” (0.152mm) is achieved, the stress/strain data is analyzed to determine the UYS of that data point.

20. MPA Load-Depth Graph/Stress-Strain Curve

21. Optical Emissions Spectrometry

22. Optical Emissions Spectrometry
OES determines the Carbon Equivalency and other elements present with concentrations / values for welding purposes.
Photons are given off by each element during the “burn” cycle and have unique wavelengths. The WL’s are measured.
From this information, the identification and concentration of each element present is calculated.
Laboratory results confirm burn depth range from ” to a maximum of ”

23. Validating Maximum OES Burn Depth
Metallographic Examination - ASTM E3-11 As Received Specimen ID: Burn Location A “Examination of the polished and etched cross section under the optical microscope revealed an observed maximum depth of penetration at the heat affected zone of burn location "A" as ". Away from the burn area, the microstructure appears normal for a carbon or alloy steel material.”
100X Magnification
500X Magnification

25. TDW’s PMI Accuracy Tolerances
Ultimate Yield Strength (UYS) +/-10%, 95% Confidence Level
Ultimate Tensile Strength (UTS) +/-10%, 95% Confidence Level
Carbon percentage (C) +/-25%, 85% Confidence Level*
Manganese percentage (Mn) +/-20%, 90% Confidence Level*
*The C & Mn results are based on Laboratory % values.

26. Chemical Analysis Tolerances

27. PMI YS/TS Tolerance Tracking Graph

28. Qualification of PMI Technicians
Min. requirements exceed Industry min’s for NDE qualifications
40 hours formal training
40 hours in field training
OQ providers are currently working to develop PMI Operator Qualification certifications

29. NDE Long Seam Identification
Using UT (Shear Wave or PAUT) can be provided the following in-ditch assessment on long seams:
Distinguish between various long seam types
AO Smith, DSAW, SAW, ERW and Lap Welded
We cannot yet make determination between high frequency and low frequency ERW, we are in the process of developing procedures to identify this information

30. New Developments A Fracture Toughness validation model is in process
Could be used in addition to determining YS / TS to give engineering a full compliment of metallurgical facts concerning their pipeline
This is achieved In-Situ, without pressure reductions
Sample pipe joints are encouraged to perform blind test on as part of our FT validation process

31. Conclusions

32. Conclusions Pipe joints have their own magnetic characteristics
Manufacture – forming of raw material
Milling – pipe joint creation process
Seamed
Seamless
Multiple data sets are useful to detect and qualify joint characteristics
Permeability
Internal Diameter
Long seam
Positive Material Identification (PMI) is capable of validating each BIN

33. Conclusions
Several years and resource investments have been made to establish a robust PMI process
Technology enables data collection, process defines success
Results have been validated by 3rd party Laboratories
PHMSA has been involved with TDW’s PMI process
Very closely involved in project that PHMSA mandated pipe properties be validated
Numerous successful blind tests
Active industry initiative to gain market acceptance as an alternate means to obtain pipe properties via NDT methods.

34. Questions