As technology advances, the sensitivity, accuracy and reliability of pipeline inspection systems improves, and ever more features are reported. This information is very useful for integrity management, but for some types of features, there remain significant challenges in classification and sizing, and for some operators, response criteria, based on previous generations of technology, can be very conservative. This leads to the question: Are we digging up our pipelines for “fun,” like a dog digging holes on the beach, or is there real value in each and every excavation?

For pipelines that are in generally good condition and subject to a limited number of well understood threats, even the historical practice of excavating at the locations of a selection of features reported by internal inspection to confirm performance is considered by some integrity managers to be a waste of resources. In other cases where numerous features are reported, concern over condition can lead to many excavations, possibly more than are needed to ensure integrity. To help make decisions on when and where to excavate, it is, in our experience, helpful to understand the full value that can be extracted from the investment in digging.

The primary reason for digging up features is of course to remove or repair defects to ensure safety, so that the required operating pressure can be maintained, and further deterioration can be prevented.

Figure 1: Type A pipeline repair sleeve.

Figure 1: Type A pipeline repair sleeve.

For longer-term integrity management, there are the other key areas to consider:

  1. Inspection system uncertainties
  2. Industry good practice
  3. Data to inform integrity management decisions

Inspection System Uncertainties

Feature type and morphology, tool speed, sensor lift, orientation, material variations, metallic debris, electrical interference, wax …. These are some of the many factors that can cause variability in the data collected by internal inspection systems. Software, data thresholding, color mapping, the number of cups of coffee drunk…. These are some of the many factors that can cause variability in the evaluation or interpretation of the data collected by internal inspection systems.

Consequently, it is common that after an inspection, there will be some features reported where there is a high degree of confidence in the classification and sizing, and other features where the classification is uncertain and sizing challenging. For these features, targeted high-quality in-field information from excavation and external inspection can help to clear up uncertainties in evaluation and can enable improved classification of other features with similar characteristics. A common example of this is seam weld manufacturing features that create reflections in ultrasonic crack detection data that are similar to the reflections caused by cracks; an example of this is shown below. For the pipeline in question, 48 crack-like anomalies associated with the long seam were identified in the preliminary UCD reporting. In-field investigation of a representative sample demonstrated that the majority were likely to be rolled-in laminations opened by the heat from the welding process. Not ideal, but as they had been subject to testing in the pipe mill and a pre-commissioning hydrotest and had shown no sign of growth during 50 years of service, they can be accepted for service without repair.

Figure 2: Rolled-in lamination at edge of seam weld

Figure 2: Rolled-in lamination at edge of seam weld.

Another example is shown below where dressing (grinding) of pipe surface flaws in the factory resulted in features with characteristics similar to a circumferential gouge in the MFL-A data. A couple of digs of representative features was sufficient to demonstrate that other similar features could be left undisturbed.

Figure 3: Possible circumferential gouge shown to be mill dressing.

Figure 3: Possible circumferential gouge shown to be mill dressing.

Good Practice

For many operators, excavating even a few locations after every internal inspection and checking the dimensions of some features and anomalies is normal to give some reassurance that the inspection results meet the service specification. This common practice is reflected in the widely adopted industry standard API 1163. This standard covers multiple aspects related to the qualification of in-line inspection systems, ranging from personnel qualifications to quality systems. A major focus is validation of the inspection system results, with the levels described. Level 1 uses historical data or limited field measurements to accept performance.
Level 2 relies on field measurements to check performance, and Level 3 requires extensive field measurements to statistically estimate performance in a given inspection. One of the major challenges particularly for Level 1 and Level 2 is selecting where to excavate to take measurements. It is natural when planning digs to target the features that are reported as the deepest, as these will be an integrity concern. This is, however, clearly not a random sample and is likely to include a disproportionate number of features where the depth has been overestimated by the in-line inspection system. Issues like this can be accommodated statistically or partially mitigated by exposing other, shallower features nearby, but they illustrate some of the challenges in validation.

A further and sometimes overlooked challenge is the potential for errors in field measurements. Measuring features manually on-site is generally expected to be more accurate than internal inspection. However, if the personnel is not appropriately trained and experienced, does not understand what the internal inspection system may have detected, and does not have appropriate procedures and equipment, significant errors are likely. Controlled studies have shown substantial variability between different inspectors in what is reported – even between the same inspector in different environments. This happens for all types of features but is probably worst for crack-like features. In our experience, a key element of good practice is to have an NDE team that is competent and experienced with pipeline features and inspection, has the right equipment and has robust procedures.

Following good practice in this way provides reassurance that critical defects will have been identified (assuming the system performed to specification) and ensures that the safety implications of out-of-specification performance can be evaluated. Other benefits of following good practice include the ability to demonstrate to stakeholders, such as regulators or shareholders, that integrity management activities are up to date.

More practically, where system performance meets specifications, continuing to use the same service provider can be justified. If system performance does not meet specifications, then an operator will need to be confident that the vendor understands why (e.g. specific, very onerous pipeline conditions), and that performance can be expected to be acceptable in the future. In the example shown below, Vendor A shows a slight systematic bias to undersize features, but good consistency. This can be easily managed by adding tolerance or by applying a correction factor. Vendor B shows a much less consistent performance, which is very hard to manage.

Figure 4: ILI system performance comparison

Information Integrity Management Decisions

An often neglected, but in my view often the most valuable, aspect of excavating the pipeline is the data that can be collected to inform and optimize integrity management decisions. This can be as simple as the very obvious benefit of repairing critical features and allowing the pipeline to be operated without pressure restrictions, and preventing continued degradation with a renewed, high-quality coating. However, multiple other benefits can be gained if a holistic approach is taken to data collection during excavations. Examples of the types of data that can be collected, and the benefits, are listed below:

  • Before digging starts, data can be collected on local infrastructure, vegetation, soil types, ground profile, agricultural activity, evidence of past excavation, evidence of ground movement, etc. This data may help with understanding what types of features (corrosion, dents, bends) may be present, and most importantly how they may have been formed.
  • During excavation, data can be collected on the nature of the soil (water content, compaction, variation between trench backfill and undisturbed ground). Again, this data can help with understanding what types of features (corrosion, dents, bends) may be present, and most importantly how they may have been formed.
  • When the pipeline is exposed, it is possible to confirm the coating type (does it match records?), evaluate the coating condition (is it damaged, wrinkled?), see evidence of past repairs and spot rocks under the pipe that may have caused construction dents. Knowing the coating type and condition really helps with managing corrosion and understanding whether cathodic protection can provide effective mitigation.
  • Coating removal quality of coating application, environment at the pipe surface, corrosion products under the coating (these are often adhered to the inside of the coating, and an experienced corrosion engineer will inspect the internal surface of the removed coating as well as the pipe surface).

Figure 5: White iron carbonate scale deposit on back of coating

Figure 5: White iron carbonate scale deposit on back of coating.

  • External inspection of the pipe: while it is important to identify and measure any features reported by the internal inspection, there is also the opportunity to check for features that may not be detectable using the system deployed. Typically when a pipe is excavated to check a corrosion feature identified by magnetic flux leakage (MFL) technology, the following additional inspections and checks can be completed:

  1. The pipe surface can be checked for crack-like features that would not be detected by MFL
  2. The seam welds and girth welds can be inspected for flaws (cracks, lack of fusion, porosity, corrosion) that may not be identifiable in ILI data
  3. Scrapings of pipe material can be taken to confirm composition
  4. Hardness surveys can be completed to characterize the heat affected zone, near the seam and girth weld

  • Once a pipe has been fully inspected, another possibility, albeit a costly one, is to cut out sections or features of interest for further examination in a laboratory. While this may seem to be an extreme response, the detailed information that can be gained from destructive testing and follow-up metallography etc. can really help to understand the situation and demonstrate very clearly to stakeholders that the threat is being managed safely.

The more we know about the environment and the condition of the multiple barriers in place to prevent failure, the better our ability to make decisions regarding future integrity management. For example, if we know that the coating has aged and disbonded, but that the soil in that area is well drained and typically dry, then we can believe predictions that corrosion rates are low in that area. The condition of the coating and the nature of the soil are pieces of information that are obvious during excavation, provided someone is looking for them and makes a record.


Digging up pipelines based on features reported by internal inspection can be costly and difficult. However, there is often substantial value to be gained from this investment. Defects can be repaired, inspection system uncertainties can be reduced, inspection system performance can be validated, and substantial data can be collected to enhance future integrity management decisions.

Figure 6: Overview of excavation site, with fewer

Figure 6: Overview of excavation site, with fewer "managers" than normal!