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IntroductionThe process o assessing the integrity o pipelines involves
carrying out a detailed study in which the sae remaining lie o
a pipeline is determined and an integrity-management plan is
produced. The ocus o such an assessment is on a metal-loss
inspection o the pipeline using intelligent in-line inspection
(ILI) tools. The inspection fndings are combined with a review o
corrosion management activities in order to diagnose the likely
causes o corrosion, or other damage, and identiy appropriate
preventative measures to minimise urther deterioration o
the pipeline. Based on determined corrosion growth rates,
predictions o uture repairs together with mitigation andre-inspection requirements can be determined. From this,
pipeline operators are able to produce an optimised inspection,
maintenance, and repair strategy in order to ensure the integrity
o their assets and extend their sae working lie while improving
pipeline saety and reliability.
This article demonstrates the important role o in-line
inspection data within the ollowing key stages o an integrity
management strategy:
• Corrosion assessment;
• Corrosion growth assessment; and,
• Remnant-lie assessment and corrosion management
strategy.
The ollowing sections describe the practical application o
each o these activities using the case study o a pipeline section
operated by Jadranski Natovod Plc, Joint Stock Co ( JANAF Plc)
in Croatia.
Background to the case studyJANAF Plc, based in Croatia, manages an international crude oil
transportation system, designed and built in the period rom 1974
to 1979, rom the port and terminal o Omišalj on the island o Krk,
Croatia, supplying both local and oreign refneries in Eastern and
Central Europe (Figure 1).
MACAW Engineering and Rosen have worked with JANAF in
developing its pipeline integrity management strategy or severalpipelines within its system. MACAW has produced integrity
assessments o these pipelines based on in-line inspections
perormed by Rosen, and one such example is presented as a
case study in this article in order to demonstrate the particular
methodologies o pipeline integrity assessment and their
application. This article has been developed in collaboration with
Rosen and JANAF.
The case study or this article concerns the 179 km long, 36 inch
diameter section o the pipeline system rom the Omišalj terminal
to the Sisak terminal. Detailed inormation was provided by
JANAF to enable a thorough assessment to be completed.
Development of integritymanagement strategies for pipelines
With the demand or energy rom an ageing pipeline inrastructure, there is an increasing need to ensure the integrity o assets and extend their sae remaining lie. Gathering sufcient knowledge about the pipeline and knowing how best toanalyse the available inormation has become critical to ensuring the long-term integrity o pipelines. Inspection using in-line intelligent tools provides the clearest picture o the condition o the pipeline. The inormation gathered rom theseinspections can then support numerous integrity related activities, including corrosion assessment, corrosion growthassessment, and remnant-lie assessment and corrosion-management strategy. This article describes the particularmethodologies and demonstrates their application using experience gained with Jadranski Natovod Plc.
By Ivan Cvitanovic, Jadranski Naftovod (JANAF) Plc, Croatia;Uwe Thuenemann, Rosen Europe BV, Netherlands; and,
Cheryl Argent, Chris Lyons, and Andrew Wilde, MACAW Engineering Ltd, UK
Figure 1: Overview of JANAF’s pipeline system. Figure 2: Corrosion concentration at a low point in the elevation prole.
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Corrosion assessmentThe aim o the corrosion assessment stage is the diagnosis o
potential corrosion mechanisms. Data relevant to the assessment
are collected, including all available inormation relating to the
basic design, operation, inspection, maintenance, and repair
inormation or the pipeline. These data include:
• Pipeline location and route (pipeline elevation profle,
satellite imagery data, etc.);
• Operational data (MAOP, MOP, product details, chemical
treatments, etc.);
• Inormation on external coating types, specifcations,
application methods and any above-ground coating-survey data;
• Cathodic protection (CP) survey results;
• Previous internal and external inspection data or the pipeline;
• Operational history and details o any repairs;
• Pipeline design and construction details (design criteria,
pipe type/grade, wall thickness, weld data, hydrotest
conditions, etc.); and,
• Current integrity-management plans or the pipeline, orexample, current inspection strategy, routine maintenance
activities, repair criteria, etc.
A review o the ILI fndings is perormed in order to ascertain
the current condition o the pipeline. By considering the shape
(such as pitting, grooving) and location o corrosion within the
line (internal, external, top-o-line, bottom-o-line, girth weld,
etc.), and the collected data on the pipeline, the likely nature
and characteristics o the reported corrosion are diagnosed. In
this way the potential causes o corrosion that are a threat to the
integrity o the pipeline can be identifed.
Case study Rosen Europe conducted a metal-loss internal inspection o
the pipeline segment rom Omišalj to Sisak during May and June
2009, using its Hi-Res MFL and XYZ mapping inspection tool
(CDG) and its Hi-Res axial aw inspection tool (AFD). The pipeline
was inspected in two separate sections: a 74.5 km section between
Omišalj and Dobra, and a 104 km section between Dobra and
Sisak. The pipeline had previously been inspected by Rosen in
2003 using its corrosion detection tool (CDP).
Internal corrosionInternal corrosion in liquid hydrocarbon pipelines usually
ollows a distinctive distribution reecting the origin and location
o ree water within the pipeline. Some o the consistent patterns
o corrosion that occur in liquid pipelines are as ollows:
• Water carry-over: water enters the pipeline as a separate
phase and creates corrosion in the bottom o the line
immediately downstream o the inlet.
• Water separation: water enters the pipeline as a water–in–oil
emulsion which breaks down over time to cause corrosion in
the bottom o the line some distance rom the inlet.
• Water pooling: the corrosion distribution in a pipeline can be
modifed by water pooling at low points whether the origin is
rom carry over or separation.
• Water hold-up: i the elevation profle o a pipeline includes
steep up-slopes in the direction o ow water hold-up can
occur at the oot o these slopes. The corrosion distribution
is similar to that or water pooling but the oil-water interace
tends to be rather more turbulent and corrosion pitting canbe concentrated at this interace.
The pattern o internal corrosion eatures within the pipeline
was consistent with water carry-over, water pooling, and water
hold-up. The corrosion had developed immediately downstream
rom the inlet, diminishing with distance, indicating water
had entered the line in a separate phase, carried-over rom the
Omišalj terminal. Local concentrations o corrosion were present
depending on the topography o the line, with the water pooling
at low points and water hold-up at the base o upslope sections.
One such concentration is shown in Figure 2, where water pooling
has occurred in the bottom o the pipeline at a low point in the
elevation profle.
The product within the pipeline has a very low water content
o 0.1–0.2 per cent volume/volume (v/v). The issues described
above are not normally seen in lines where the water content
is below 0.5 per cent v/v, and it was thereore concluded that
the distribution o internal corrosion eatures in this pipeline
may have been caused as a result o operational issues at some
stage during the lie o the pipeline. Indeed, during the period
o wartime rom 1991–95 the pipeline was let dormant with
the product shut-in. Such conditions would have undoubtedly
avoured corrosion via the pooling o water. Consequently, it was
considered likely that the internal corrosion eatures were no
longer active. This was investigated in detail during a comparison
o the two sets o inspection data and the fndings are discussedlater in this article.
External corrosionThe pipeline is protected against external corrosion by an
external coating and an impressed-current CP system. The
coating on the longitudinally-welded sections o the line is mill-
applied Densolene polyethylene, whereas or the spirally-welded
sections the coating was feld applied. Polyken tape was used
locally where repairs have been made.
The majority o external corrosion was reported in the bottom
hal o the pipeline and located in the spirally-welded sections
where a feld-applied tape coating had been applied. JANAF’s CPmonitoring had shown that adequate protection levels were being
achieved and thereore the most likely cause o the corrosion was
CP shielding which occurs in areas where wrinkling or sagging Figure 4: Example demonstrating search window technique to account
for location reporting accuracy.
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o the tape coating allows water and soil ingress beneath the
coating. The CP system can become shielded rom the active
corrosion by the coating.
A concentration o external corrosion was associated with
an above-ground section o line where the pipeline was not
protected by the CP system and the external paint coating was
the only orm o corrosion protection. Consequently, any coating
deects in this area would have been at risk rom atmospheric
external corrosion and it is likely that this was the cause o the
corrosion concentration. The corrosion in this area was identifed
at an early stage and the corrosion had not impacted on the
integrity o the pipeline.
JANAF indicated that the pipeline was subject to stray current
intererence rom numerous DC railway crossings. Stray currents
can represent an external corrosion risk and it is understood
that the pipeline was directly aected up to a distance o
approximately 50 km and indirectly inuenced up to a distance
o approximately 100 km. To proactively counteract these eects
JANAF perormed a modernisation o the pipeline CP systemby installing remote-controlled transormer-rectifer (T/R) units
along the line in order to prevent corrosion in these areas. A key
requirement o the inspection comparison was to review the
eectiveness o these mitigation measures by confrming the
extent o any corrosion activity in these sections o the pipeline.
Corrosion growth assessmentThe corrosion growth assessment (CGA) was conducted in
three stages:
• Feature matching;
• Inspection signal comparison; and,
• Detailed eature resizing.
Each stage o the CGA process is described in detail below.
Feature matchingFeature matching involves the automatic comparison o
two or more sets o inspection data using the eature list
rom each inspection. Beore repeat sets o inspection data
can be compared, they must frst be aligned to a common
‘master’ distance. To ensure sucient accuracy in the distance
correlations, each girth weld should be matched in both o
the inspections. Aligning two sets o data using other pipeline
eatures such as valves, tees, or bends may not provide a
suciently-accurate distance correlation.
Once the inspection data sets are aligned, they can be
compared to identiy eatures that have been reported in both
inspections. For each corrosion eature reported in the recent
inspection, the previous inspection data was reviewed to generate
a list o possible matches. This process takes account o the
errors associated with the axial and circumerential positions by
defning a search window around the eature.
Feature matching provides a quick way o comparing repeat
sets o inspection data and can provide useul inormation that
is applicable to the whole pipeline, not just a sample o the
reported eatures. However, all inspection tools contain a degree
o variation which will aect the accuracy o the inormation
obtained rom a eature matching exercise. Variations include:
• Reporting threshold/detection capability;
• Feature-sizing accuracy; and,
• Axial and circumerential location accuracy.
Unless the above actors are considered within the corrosion-growth comparison, they can result in incorrect matches and
unrealistic corrosion rates. Each actor is discussed below.
The next stages o the corrosion-growth assessment (signal
comparison and detailed resizing) are aimed at removing or
reducing the aect o these variations, and improving the
accuracy o the CGA, and are described in the ollowing.
Reporting threshold/detection capability Inspection results tend to have a reporting threshold (typically
10 per cent wt) imposed upon them due to the large number
o shallow metal-loss indications recorded. In addition, the
sophistication o ILI tools has increased dramatically since their
introduction approximately 40 years ago; consequently, their
ability to detect a given eature has also improved. Both o these
points should be considered when using the results o eature
matching, since eatures that have been reported or the frst
time may have been present but not detected or reported by the
previous inspection; they may not necessarily have grown.
This uncertainty is dealt with by conducting stages 2 and
3 o the CGA process – signal comparison and detailed eature
resizing.
Figure 4: Normalised signal amplitude based on xed reference
points such as girth welds. Figure 5: Signal comparison example.
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Feature-sizing accuracy Currently, ILI tools typically report general corrosion with
an accuracy o +/-10 per cent o the wall thickness with a
confdence limit o 80 per cent, i.e. 80 per cent o the time, the
reported depth will be within +/-10 per cent o the actual eature
depth.
The accuracy o a comparison o the depths o a eature
reported in two inspections is dependent on the sizing accuracy
o both tools. An increase (or decrease) in the reported depth
o a eature between inspections can thereore be attributed to
either real corrosion growth or to a variation in depth sizing in
each inspection.
The sizing accuracy o each tool can be used to calculate
the minimum corrosion rate that would be considered to be
statistically signifcant. Below this statistically-signifcant limit,
an increase in reported depths can be attributed to either real
corrosion growth or just variation in the sizing.
For example, consider a general corrosion eature1 located in
10.31-mm wall thickness pipe reported in both 2003 and 2009.Assuming both inspection tools have a depth sizing accuracy o
+/-10 per cent wt at 80 per cent confdence, then the accuracy
o the calculated corrosion growth rate is +/-0.22 mm/a (95 per
cent confdence level). This accuracy can be improved upon
by conducting stage 3 o the CGA process: the detailed eature
resizing.
Axial and circumferential location accuracy The location accuracy is dealt with in two ways in the eature-
matching process: frstly by aligning the eatures in terms o
reported distance, and secondly by using a search window
to match eatures reported by the previous inspection, as
illustrated in Figure 3.
In addition, inspection vendors dier on how they report
eature locations. For example, some vendors use the top let
corner o the eature ‘box’ (as seen in Figure 3), while others
report the centre o the ‘box’. When comparing multiple vendor
inspections the eature data should be adjusted so that all
inspections are reerencing the same location.
Inspection signal comparisonThis stage o the CGA involves the comparison o the raw
inspection signals in order to validate the growth rates
calculated by the eature matching process. Areas selected
or signal comparison include areas o high corrosion growth,apparent ‘new’ growth, and corrosion ‘hotspots’. The signal
comparison eliminates some o the uncertainties related to
the eature-matching process. It is possible to confrm whether
eatures identifed as ‘new’ by the eature matching were in act
present at the time o the previous inspection, although not
reported as they were sized below the reporting threshold. The
signal comparison also validates the matching process.
In order accurately to compare MFL signal data, it is
necessary to normalise the signal amplitude based on a fxed
reerence point (i.e. eatures that will not have changed between
inspections), such as eatures that have been repaired by
composite wrap, eatures that have been recoated immediatelyater the previous inspection, artifcial deects, or girth welds,
(see Figure 4). The signal comparison is not limited to same-
vendor inspections; however, additional data manipulation may
be required such as re-orientation o the signals.
An example signal comparison is shown in Figure 5 that
shows growth o existing and new eatures.
Detailed feature resizingIn this stage, a selected number o eatures identifed in the
earlier stages are subject to detailed analysis and resizing in
order to ensure equivalent interpretation o the inspection
signals in both inspections. This stage makes use o the latest
sizing model and algorithm compensation, and takes into
account the assessment o systematic errors and a calibration
correction. These processes are discussed in urther detail
below.
It should be noted that this process is conducted by the
inspection vendor as access to proprietary sotware and sizing
models is required. This type o analysis is only possible or
repeat inspections by the same vendor.
Interpretation of inspection signalsPart o the data-analysis process or a given eature involves
the interpretation o the shape o the MFL signals. In certain
instances, there may be more than one plausible interpretation:
or example, a certain MFL signal shape could be caused by
either one, wide eature or by two very close pinhole eatures.
A dierence in the interpretation o a given signal can result in a
dierence in reported depths.
Sizing model and algorithm compensation
Sizing models and sizing algorithms are regularly reviewedand improved based upon additional pull-through tests and
in-feld verifcation data. The use o dierent sizing models or
algorithms can result in small sizing dierences. Thereore the
older sets o inspection data are re-analysed using the latest
sizing models and algorithms.
Assessment of systematic errors and calibration correctionIn addition to the small inuence rom varying sizing models,
each ILI is aected not only by scattering o results, but also by
small shits or osets o the calibration, and these are reerred
to as systematic errors. These are corrected using verifcation
data and eatures known to have remained the same between
inspections, such as repaired eatures, artifcial deects andmilling eatures.
The detailed resizing process described above signifcantly
improves the accuracy o the calculated growth rate. This
is demonstrated by the example quoted previously where
a corrosion growth rate calculated by the eature-matching
process would have an accuracy o +/-0.22 mm/a. The corrosion-
growth rate associated with this same eature ollowing detailed
resizing would have an improved accuracy o +/-0.09 mm/a
(at 95 per cent confdence).
Corrosion growth assessment summary
Each stage o the CGA improves upon the accuracy o theprevious one. Feature-matching gives an indication o areas o
1. As dened by Pipeline Operator’s Forum ‘Specications and requirements for intelligent pig inspection of pipelines’, January, 2005.
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highest activity, and matched eatures give a good indication
o the actual growth rate. However unmatched eatures can
give an overestimate o corrosion rate as they may not be new
growth but existing eatures that were below the reporting
threshold o the previous inspection.
The signal comparison stage can confrm whether unmatched
eatures are in act evidence o new growth and eliminate any
erroneous high rates. However, the signal comparison is still
dependant on the sizing accuracy o both inspection tools. The
detailed eature resizing ensures equivalent interpretation o
the inspection signals and reduces the associated sizing errors,
thus signifcantly improving the accuracy o the calculated
corrosion rates.
Case study In the CGA conducted on JANAF’s pipeline all eatures were
included in the eature-matching process, the signifcant areas
o corrosion growth identifed by eature matching were then
subject to signal comparison. From the fndings o the signalcomparison 101 eatures were selected or detailed resizing.
The CGA revealed that there was no evidence o internal
corrosion growth throughout the pipeline, thus confrming
the conclusions o the corrosion assessment that the internal
corrosion occurred was historical and most likely occurred
when the pipeline was shut-in with product.
There was no evidence o signifcant corrosion growth in the
areas believed to be aected by stray current. This confrmed
that the control measures implemented by JANAF were
mitigating the problem.
The CGA confrmed evidence o external corrosion growth in
the spiral-welded sections o pipe where a feld-applied tape
coating was used. As described previously, the CP monitoring
data indicated that adequate protection levels had been
achieved, and thereore the most likely cause o this corrosion
was CP shielding. Low-level corrosion growth was identifed
on the above-ground section that was not protected by the CP
system.
Pipeline segmentationLocal variation in ground and coating conditions along the
pipeline route will lead to a variation in the rate o external
corrosion growth. To reect this variation, the pipeline was
segmented or the application o corrosion growth rates in the
uture integrity assessment. The maximum growth rates oreach segment were applied to all reported eatures within that
segment. It is understood that the majority o eatures will grow
at corrosion rates less than the maximum rate. However, the
highest corrosion rates were confrmed during the CGA and due
to the random nature o corrosion growth, it was not possible to
identiy eatures that may grow at these high rates in the uture.
The segmentation was driven by the ollowing contributing
actors:
• Corrosion concentrations (hotspots);
• Corrosion growth rate;
• Changes in consequences area;
• Pipeline topography;• CP data;
• Soil-resistivity data;
• Changes in coating type; and,
• Changes o pipe manuacturer.
Future integrity and corrosionmanagement strategy
Based on the fndings o the corrosion assessment and CGA
described above, an eective uture integrity and corrosion
management strategy can be developed.
The corrosion growth rates are applied to the eatures, which
are then assessed in terms o their impact on the immediate
and uture integrity o the pipeline using relevant code
guidance (or example, Modifed B31G, Detailed RSTRENG2).
Deect-assessment techniques are not described in detail within
this article. A schedule o uture repairs is generated by this
process.
The active corrosion mechanisms identifed by the corrosion
assessment and CGA enable an appropriate mitigation/
rehabilitation strategy to be developed. In the case o JANAF,the active corrosion mechanisms identifed were CP shielding
and atmospheric corrosion on the above-ground section where
the pipeline cannot be protected by the CP system.
The above-ground section was investigated and active
external corrosion was identifed. This was mitigated by sand
blasting and application o an improved paint coating system
in the aected areas.
It was not possible to mitigate against CP shielding thereore
a sectional recoating/replacement schedule was developed
based on calculated time to repair or individual eatures. In
most cases sectional recoating prior to the date by which the
eatures would require repair is a more cost-eective solution
than repair.
ConclusionsThe main conclusions o this article are:
1. The good communication links set up between
operator, inspection vendor and consultant were
key in developing a ocused and eective integrity-
management strategy.
2. The comprehensive historical and current pipeline
data provided by JANAF enabled accurate diagnoses o
corrosion mechanisms.
3. The detailed corrosion-growth assessment clearly
identifes the active and dormant corrosionmechanisms.
4. A very high degree o accuracy or calculated corrosion
growth rates can be achieved by conducting signal
comparison and detailed resizing.
5. The assessment conducted by MACAW demonstrated
that the internal corrosion mitigation and stray current
mitigation implemented by JANAF were eectively
controlling corrosion activity.
6. The detailed corrosion-growth assessment together
with the detailed pipeline data allowed pipeline
segmentation o high risk and high growth areas or
appropriate application o growth rates in the utureintegrity assessment.
2. PRCI Report PR 3-805 ‘A modied criterion for evaluating the remaining strength of corroded pipe’ 22nd December, 1989.
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7. The corrosion assessment and corrosion growth
assessment build up a very clear picture o the current
condition o the pipeline and can be used to predict the
uture condition o the pipeline and any repairs and
rehabilitation that may be required.
8. In most cases, it is more cost-eective to prevent or
limit urther growth by implementing corrosion-control
measures than it is to conduct repairs. Mitigation can be
targeted at the active corrosion mechanisms identifed by
the assessment and a re-inspection interval can be set to
confrm the eectiveness o such actions.
This article was presented at the Pipeline Technology
Conerence held in Hannover, Germany, in April 2010, and
organised by EITEP.