NDT Global welcomes you to the

19th Pipeline Technology Conference

Join us at the forefront of innovation as we return to the Pipeline Technology Conference (PTC) in Berlin, Germany, ready to dive into a world of learning, collaboration, and exploration of the latest tools and technologies shaping the industry.

Swing by our booth H14 to explore, connect, and envision the future of pipeline integrity. Your journey into innovation starts with NDT Global.

Explore: Navigate the future of pipeline integrity with NDT Global, where our advanced ultrasonic technologies redefine standards.

Experience: Immerse yourself in our 3D interactive tool models, offering a hands-on glimpse into the cutting-edge solutions driving pipeline excellence.

Connect: Meet the faces behind the innovation – our passionate team is eager to share insights, answer questions, and forge meaningful collaborations.

Let's make PTC 2024 a hub of knowledge, collaboration, and discovery. See you at our booth!



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The Impact of Innovation.

Upcoming Presentations

Don't miss our insightful presentations! Check out the schedule below for details on when and where our papers will be presented.

Headshots PTC 2024


Christoph Seeber

Project Lead, Data Analysis UM

Successful Detection and Sizing of Girth Weld Metal Loss Features

Session 1.2 Inline Inspection and Integrity Management

Date and Time: April 10, 9:00 a.m.

Authors: Christoph Seeber, Kerstin Munsel, Thomas Meinzer, Christiane Rahner, Sayan Pipatpan


NDT Global’s pulse echo metal loss technology with quantitative wall thickness measurement and pitting/pinhole resolution provides reliable detection of metal loss features in and around girth welds. Representing state-of-the-art electronics and incorporating high-resolution sensor carriers, this innovative technology identifies features in the heat-affected zone (HAZ) and directly in the girth weld without issues.   

Compared to data acquisition in the straight parts of a pipe joint, a true detection and recording of girth weld features strongly depend on the nature of the girth weld, e.g., its texture, and finishing. During an inline inspection, these conditions can influence the passage of a sensor carrier when crossing a girth weld. 

This paper aims to highlight the impact of the girth weld character on the data recording and data analysis while showing how different the pallet of external and internal metal loss features in and at girth welds can be, partly with severe depths, and how they can be identified in the analysis.  

Headshots PTC 2024 (1)


Victor Ferrer,

Senior Machine Learning Engineer

How Deep Learning Changes Ultrasonic Metal Loss Analysis - An Inline Inspection Industry Template

Session 1.3 Inline Inspection and Integrity Management

Date and Time: April 10, 11:15 a.m.

Authors: Victor Ferrer, Katja Träumner, Thomas Meinzer, Christiane Rahner


Ultrasonic metal loss technology is a premium inline inspection technology providing high-resolution direct wall thickness measurement. The underlying principle is used to deliver profound insights into a pipeline state in terms of corrosion (also channeling corrosion) and lamination features. The high sensitivity of the technology enables the detection of complex features but also is prone to effects due to challenging pipeline complexities. Highly trained analysts follow well-defined processes to distinguish between safety critical features and "noise" effects, here automated algorithms are challenged.  

Using automated feature detection in inline inspection (ILI), the requirements are strict. The rate of non-detected relevant features needs to go against zero (no false negative), as they represent safety risks. Simultaneously, false call rates by the algorithm (false positives) should not be too high to provide a valid input for manual data analysis or a direct report for the customer. 

Deep Learning technology, an artificial intelligence method, has become a standard tool for complex image recognition in the last few years. Mimicking complex human pattern recognition has been successfully applied in many fields. Therefore, it has a lot of potential in complex ILI analysis like ultrasonic metal loss measurement which relies heavily on human capabilities. 

In this paper, we present a new automatic feature detection approach for ultrasonic metal loss technology based on deep learning. We will outline the approach we followed in the case of model selection and training, the evaluation process established to assure process safety, and the system and process integration. In doing so, we provide a complete industry example and template for using state-of-the-art machine learning technology in complex ILI.  

Headshots PPIM 2024 (2)


Willem Vos,

Senior Technical Specialist

Review of Lessons Learned from 10 Years of Ultrasonic Inspections in Gas Pipelines

Session 3.4 Difficult to Inspect

Date and Time: April 10, 2:00 p.m.

Authors: Willem Vos


In the early 21st century, a team of researchers in DNV (Norway) developed an ultrasonic technology for the inline inspection of gas pipelines without using a liquid batch. The technology has subsequently been used to inspect more than 15,000 kilometers of operational gas and liquid pipelines around the world.

The authors are presenting a review of lessons learned during the deployment of this new technology and reflecting on the advantages and limitations.
A summary is presented of validation work completed, both through pull testing and field excavations.

Several different use cases are considered; one being the deployment of acoustic resonance ILI for the baseline inspection of newly constructed gas pipelines. In particular, the others will highlight a number of long-distance gas transmission pipelines that have been inspected using acoustic resonance ILI, and highlight the benefits of ultrasonic baseline for pipelines.
Furthermore, the tools have shown notable flexibility in the field of difficult-to-inspect gas and liquid pipelines. Notably, large diameter variations have been traversed, and bidirectional inspections have been performed, as well as extremely long-duration runs.

A summary of completed work will be of value to all pipeline operators of challenging pipelines, in particular offshore, demonstrating challenging pipeline inspection projects that have been completed successfully.

Headshots PTC 2024 (2)


Christoph Jäger,

Senior Pipeline Integrity Engineer

Enhancing Pipeline Integrity: A Comparative Study of Ultrasonic and Magnetic Flux Leakage Inspection Technologies

Session 1.5 Inline Inspection and Integrity Management

Date and Time: April 10, 4:50 p.m.

Authors: Christoph Jäger, Katherine Hartl


Inline inspection (ILI) plays a pivotal role in pipeline integrity management programs. While ultrasonic technologies (UT) have been a part of ILI vendor portfolios for decades, many operators exclusively rely on magnetic flux leakage (MFL) technology for metal loss inspection. This paper explores real-world experiences highlighting the integrity advantages gained from using UT alone or in combination with MFL, emphasizing the importance of incorporating an off-cycle technology during re-inspections that utilizes a different measurement principle.

The choice of ILI technology depends on factors such as anticipated threats, pipeline conditions, and parameters, which ultimately shape the desired outcome. Additionally, this paper elucidates the distinctions between UT and MFL ILI technologies concerning operational constraints, anomaly detection, sizing, and associated analytical differences. These insights are substantiated by extensive collaboration with a pipeline operator across multiple liquid pipeline assets.

The Promise of Insight.

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