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Many existing pipelines were never designed for intelligent inspection, yet their reliable assessment remains essential. This paper uses six real-world examples to demonstrate how inspections can be achieved even under difficult or non-standard conditions:

Turnkey inspection of a 10" gas storage pipeline: Cleaning, intelligent inspection and commissioning completed within just one week

Time is money: Short notice MFL inspection of two out-of-service sour gas pipelines with expedited data analysis

Pre-commissioning inspection in compressed air: 36" transmission line in the Rocky Mountains inspected with 3PⁿX technology at only 10 bar, a long-distance pipeline was successfully inspected at low pressure using an optimized low-friction tool design and sensitive 3PⁿX sensors to ensure complete data acquisition under non-standard conditions.

Pig launch from a three-way valve: Product line inspected without a conventional launch trap using a specially adapted tool

Inspection of a 3" pipeline in Indonesia (32 km): Extremely small internal diameter and long distance across dense jungle terrain, difficult access, and a history of stuck pigs. A lightweight, low-diameter tool design with increased bypass and robust contingency planning ensured a complete and safe inspection.

Advanced Multi-Sensor Tool: Accurate differentiation between debris and corrosion (MFL, GEO, 3PⁿX), a 286 km heavy-wall pipeline with a significant debris history required a custom magnetizer and a multi-technology inspection tool. The combination of MFL, geometry, and 3PⁿX sensors enabled reliable discrimination between debris, internal corrosion, and corrosion under debris.

Many owners of challenging pipelines have been told for years that they have ‘Unpiggable’ pipelines, leading them to resort to a combination of external inspection techniques and hydrotesting to ensure the integrity of these critical assets. This is a major problem for pipeline operators as high-quality inspection data, that covers the entire pipeline, can be a requirement for the operating license or to implement a maintenance program that limits the risk of uncontrolled product releases.

However, truly ‘Unpiggable’ hardly exist anymore. Modern ILI tools have a large operating envelope and can be tailored for specific pipeline conditions. To inspect these challenging lines, three things have to come together: the will and the need to inspect, sufficient time to prepare for the inspection and sufficient funding. While the initial investment in time and money can be higher; this investment repays itself with repeat inspections and improved Pipeline Integrity Management.

For challenging pipelines sending an RFQ to a couple of vendors and expecting a complete proposal normally does not work. Approaching the project as a joint-venture with team involvement and buy-in from several departments will provide a better solution. The asset owner, should be prepared to engage their Integrity team, Operations, Planning, Shipping, etc. On the ILI Supplier side, it starts with a Technical Advisor - not a salesperson - who understands the challenge and brings together a team to deliver a comprehensive solution. This may include Engineering, Operations and Analysis. This is challenging to organize, but the long-term rewards, financially and integrity wise can be well worth the investment in time, effort and resources, resulting in a successful ‘unpiggable’ inspection.

Wax deposition is a known driver for under-deposit corrosion, often creating conditions for microbiologically influenced corrosion (MIC), particularly from sulphate-reducing bacteria (SRB). This paper outlines the corrosion management approach adopted across the Asset following the failure of the 8-inch oil pipeline, where ineffective cleaning and wax build-up contributed to internal corrosion and loss of containment.

An accelerated intelligent pigging (ILI) campaign was carried out to assess pipeline condition and support fitness-for-service decisions. Prior to inspection, the pipeline underwent extensive cleaning using 13 dual-module brush pig runs, with e-Splora™ sensorised pigs deployed to verify cleanliness and confirm readiness for inspection, ensuring reliable ILI data.

In parallel, ILI supported the repurposing of the 8-inch pipeline from water injection to oil production service, establishing an integrity baseline and operational confidence.

A revised corrosion management strategy for repurposed oil production focused on optimised pigging frequency, improved pig design, and cleanliness verification. Transition from single- to dual-module brush pigs improved removal of adherent wax deposits, while high-frequency pigging ensured effective corrosion inhibitor distribution.

The use of e-Splora™ provided a cost-effective method to monitor wax distribution and cleaning performance, enabling data-driven optimisation of pigging campaigns.

Routine wax and fluid sampling, including SRB monitoring, confirmed no significant microbiological activity, demonstrating that effective cleaning combined with continuous corrosion inhibitor injection can mitigate MIC risks.

Overall, this work shows how ILI, targeted pigging strategies, sensorised monitoring, and SRB verification provide a robust and practical framework for managing wax-induced corrosion in ageing and repurposed pipeline systems.

Subsea pipeline integrity inspection is becoming increasingly challenging as operators manage pipeline systems with non-conventional configurations and demanding inspection conditions. These challenges may include internal diameter variations, high wall thicknesses, complex geometries, small-radius bends, diameter transitions, and Y-junctions. Such characteristics impose significant limitations on conventional in-line inspection (ILI) tools, which are often not designed to safely negotiate major internal restrictions, abrupt geometry changes, or highly constrained subsea layouts.

In this context, full-scale testing in specialized facilities is an essential step for technology qualification and operational risk reduction. By replicating field-representative conditions, including hydraulic transients, physical restrictions, and complex layouts, controlled testing enables rigorous assessment of tool passage, mitigation of stuck-pig risk, and improvement of First Run Success probability. It also allows verification of sensor response, data quality, and detection performance before field deployment.

This paper presents case studies showing that collaboration between operators, CTDUT as the technology center, and PipeWay as the ILI service provider, combined with full-scale pre-deployment qualification, provides a safer and more efficient pathway for assessing unconventional pipeline systems without requiring structural modifications to the asset.

As offshore infrastructure matures, the industry faces increasing demands for efficient pipeline cleaning, both for In-Line Inspection readiness and for re-purposing or decommissioning of existing assets.

Conventional cleaning strategies can be highly time-consuming, particularly in pipelines characterized by extensive wax deposition, LRA accumulation, or limited accessibility. These challenges are further compounded in systems incorporating flexible components, where the use of conventional mechanical cleaning tools such as metallic scrapers or brushes is typically not feasible.

This paper introduces steam-assisted flushing as an innovative approach that revisits and extends established topside cleaning principles into subsea pipeline applications. The approach is based on the controlled application of elevated temperature fluids to enhance the removal and mobilisation of deposits, thereby improving overall cleaning efficiency.

Engineering studies, combining fluid- and thermodynamic considerations with operational results and experience from long-distance pipeline flushing using heated fluids, demonstrate that subsea temperatures in the range of 50–60°C can be achieved and maintained over significant distances, enabling enhanced performance of both mechanical and chemical cleaning processes.

The paper further evaluates system requirements for offshore heat generation and transfer, as well as operational implications such as reduced offshore vessel time, lower environmental footprint through decreased chemical usage and the potential for earlier/improved handling of NORM and LRA residues in pipelines during decommissioning.

A storage terminal operator in the UK wanted to bring a “mothballed” jet fuel pipeline back into operation and needed to understand the condition of the line before returning it to service.

Prior to the line being mothballed, Intero had previously inspected the line using its free-swimming UT ILI fleet; however, at the time of the desired inspection, a number of challenges would be present which made the line difficult to inspect such as:

• ongoing maintenance work at the terminal

• inability to install receiving equipment

• an unbarred tee at the 6 o’clock position shortly after launch, and

• a physical obstruction to access the line at the launch location.

Using the Pipe Explorer MFL Robot, Intero was able to successfully inspect the line over two mobilizations which included:

• crawling through a 5m vertical launch

• navigating into and out of the unbarred tee piece

• overcoming thick girth welds causing unexpected battery drain

• encountering unanticipated liquids in the line, and

• introducing a nitrogen blanket to ensure safe operations following lessons learned during the first mobilization.

This paper and presentation will expand upon the lessons learned during the first mobilization and explain how the Pipe Explorer MFL Robot was able to address each of the challenge features in order to ensure a safe and successful inspection in the end.

In-line inspections (ILIs) are a well-practiced and vital technique for understanding integrity of the full length of a pipeline. Going beyond a single ILI and performing multiple ILIs with sufficient time gaps between them allows for the change in the pipeline integrity over time to be understood by the matching of defects present across the ILI datasets (often from different vendors and technologies). This allows for corrosion growth rates to be calculated and the current and future pipeline integrity to be assessed. This matching process requires the handling of large amounts of data and has historically been done manually through the expertise and judgement of engineers. This is a time-consuming and tedious process that either requires the commitment of days to weeks to match the full dataset or to compromise and only match key defects of interest.

Irth has developed a platform to centralise and analyse pipeline integrity data which includes an innovative approach to the handling of ILI data. The approach involves the use of machine learning to ingest the data (regardless of differences in vendor formats), align the data across ILIs, match defects and calculate the corresponding corrosion growth rates.

This paper will focus on the implementation of machine learning for analysis of ILI datasets and the experience of Jee using this process to improve the veracity of pipeline remnant life studies thereby increasing the confidence of pipeline operators in the integrity of their assets and efficiency of the process.

Magnetic Flux Leakage (MFL) inspection begins with a straightforward premise: saturate the pipe wall, measure the escaping flux, and translate the signal into metal-loss characterization. In controlled calibration environments, the physics behaves exactly as expected—flux paths remain stable, sensor coupling is consistent, and defect responses align cleanly with established signal-response models.

Once an MFL tool enters an operating pipeline, the magnetic system becomes a dynamic story rather than a static equation. Speed excursions disrupt magnetization equilibrium, lift-off weakens sensor coupling, debris alters flux closure, and wall-thickness transitions reshape the magnetic circuit. These interactions generate signatures that diverge from idealized models and challenge deterministic interpretation.

In this real-world narrative, analysts act as both physicists and interpreters. They must separate true metal loss from transient artifacts, magnetization instability, and noise structures that mimic legitimate features—while respecting tool-specific sizing limits and the operator’s risk posture. Two qualified analysts may reach different yet defensible conclusions, reflecting the inherent complexity of magnetic behaviour under dynamic conditions.

This paper explores the relation between physics-based modelling with contextual interpretation. By defining where deterministic models end and expert judgment begins, the approach strengthens analytical consistency, improves defensibility, and supports more confident integrity-management decisions.

Circumferentially oriented stress corrosion cracking (CSCC) can develop in pipelines when residual axial or bend stresses are induced as result of construction practices or geotechnical stability issues exceed hoop stress, it can show itself particularly in areas with coating damage or compromised cathodic protection. Conventional inline inspection (ILI) technologies often fail to detect CSCC, requiring direct assessment approaches based on susceptibility criteria.

This paper presents a high-resolution approach combining axially oriented magnetic flux leakage (AMFL), circumferential MFL (CMFL), and a new IDD-SM (Internal Depth Detection with Stress Measurement) sensor system. IDD-SM models elevated stress around cracks and crack-like features, correlating stress with local magnetic property changes to improve detection and characterization.

Initial testing used 6.625-inch diameter pipe sections with known CSCC, removed from service and re-inspected in multiple pull tests to compare signal responses under increasing bending moments. An IDD-SM algorithm quantified and ranked CSCC colonies, integrating AMFL and CMFL results to optimize probability of detection, identification, and sizing.

The system successfully detected 90° circumferential and off-axis or angled SCC (45°–90° from the axis of the pipe) and measured crack skew angles with ±10° accuracy. Subsequent data analysis provided a robust method for assessing pipeline integrity and prioritizing repairs where traditional diagnostics are insufficient.

Since initial testing was performed in 2017, this ILI system has gone on to successfully detect and identify more than 1000 cracks in North America, has been deployed in Latin America and in Europe. Re-inspections have also been successfully carried out providing crack growth analysis in a run-to-run comparison, followed by field verification and confirmation.

EMAT + High-Resolution Tri Axial TFI advanced tool allows for precise detection of axial SCC / crack like features, and Metal loss in a single run. The two technologies running simultaneously allow for synchronized data collection and analysis by the same analyst (certified in both technologies), hence improving the probability of identification. Recent enhancements to the mechanical design of the EMAT tool include individual suspension of the EMAT coils, reduced magnetic drag and improved structural robustness of the tool.  The individual suspension has improved the efficiency and stabilized the acoustic coupling of the EMAT coil to the pipe metal. The reduced magnetic drag has improved the motion stability and speed control of the tool while the structural robustness ensured successful runs with minimal tear and wear on the tool. Additional improvements include wider use of artificial intelligence for defect recognition and sizing based on advanced neural networks.

Results from recent successful deployments in two European countries followed by successful field verifications will be presented.

Utilizing the combined technologies (EMAT + high-resolution Tri Axial TFI) in a single tool run is proving to be a better design resulting in enhanced probability of identification at a lower cost of inspection and less interruption to operations when compared to two separate inspections of “EMAT + Transverse magnetic flux leakage”.

This paper describes a joint case study by EQUINOR and RPC-Tec on the internal cleaning of the Sleipner-Kårstø condensate pipeline system prior to in-line inspection. The 20-inch, 248 km pipeline has been in operation since 1993 and during inline inspections in 2012 and 2014 exhibited reduced ultrasonic echo quality in large parts of the pipeline, limiting inspection confidence and creating uncertainty in the interpretation of wall-condition data. EQUINOR’s objective was to execute safe, controlled cleaning operations and prepare the line for reliable UT inspection by improving the internal cleanliness of the system.

EQUINOR defined a clear operational objective: to achieve reliable, first-time-cleaning performance that would support safe pigging operations and improve the quality of inspection data. Previously used cleaning pigs had not been sufficient to fully address the identified issues, particularly in relation to deposit removal and the limitations affecting data return in the landfall area. State of art RPC mechanical cleaning tools were introduced to supplement the cleaning programme and target the

challenging internal conditions observed in the line. The paper discusses how tool design, differential pressure behaviour, flow conditions, and pipeline-specific constraints influence cleaning effectiveness and the quality of In Line inspection data collected.

The case shows that successful pre-inspection cleaning is not simply a matter of running more pigs, but of using a defined inspection objective, deposit-aware tool design, and close coordination between EQUINOR and RPC-Tec. The experience from Sleipner-Kårstø offers practical lessons for operators facing similar echo-loss and data-quality challenges in mature pipeline systems.

Increasing demand for efficient inspection of pipelines with varying internal diameters has driven the need for adaptable in-line inspection (ILI) solutions.

Conventional ultrasonic wall measurement (UTWM) tools are typically optimized for a single diameter, limiting their applicability in multi-diameter or constrained pipelines.

This paper presents the full lifecycle development of a compact, bi-directional (BiDi) 10″–12″ UTWM tool, designed to overcome these limitations while maintaining high-resolution metal loss inspection performance.

The tool integrates a compact 1000 mm design with a neutral buoyancy concept to minimize friction and enable stable operation at very low flow rates and differential pressures.

Key engineering challenges addressed include sensor carrier adaptability, passage performance across varying internal diameters, and maintaining data quality under fluctuating operational conditions. Manufacturing considerations focused on achieving robust yet lightweight construction, ensuring repeatability and reliability.

Validation was conducted through extensive largescale pump testing, demonstrating consistent tool velocity, reliable passage through complex pipeline features, and compliance with API 1163 performance standards in both diameters. The results confirm that the multi-diameter UTWM tool delivers high-quality corrosion data while significantly improving operational flexibility for pipeline operators.

Accurate corrosion growth rate (CGR) estimation from successive in-line inspections (ILI) relies on run comparison (RC), where algorithms match anomalies between inspections. Incorrect anomaly pairing can exaggerate delta‑depth statistics and lead to overly conservative CGR estimates, which in turn increase the number of scheduled responses and result in inefficient and costly remediation plans. This effect becomes particularly pronounced for deep and complex corrosion populations and in projects where signal‑based confirmation is unavailable, making integrity decisions heavily reliant on RC algorithm behaviour.

This paper presents and tests a workflow for tuning RC software configurations using a large synthetic dataset. Building on a previously developed validation framework, a larger and more representative library of corrosion scenarios was constructed to stress‑test RC behaviour. The performance of different RC software configurations was then compared on synthetic and real-world data.

The primary outcome is a strong correlation between configuration rankings obtained from synthetic data and those observed on real‑world data. These results support the use of synthetic datasets as a practical proxy for RC tuning when ILI data are unavailable. Additionally, a possible RC performance specification format, expressed as a function of corrosion complexity, is discussed.