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Pipeline Technology Journal - 3/2024 This Issue’s COMPLETE CONTENT 18 Insights Bats, Bees, Snakes, Octopuses, and Pigs! M. Kirkwood 26 Hazard Based Protection of Gas Infrastructure Facilities against Cyber-Physical Attacks M. Bächle, J. Schmidt 30 40 New Generation of AI Techniques Applied to Third Party Interference and Leak- age Detection on Pipelines A. P. Gomes, M. Marino, M. Biagini, F. Chiappa From Pipelines to Home Heat- ing: The Digital Transformation of Natural Gas Distribution S. Şenol, S. Bilim, Ö.F. Güner, M.H. Çevik   Pipeline Technology Journal - ptj www.pipeline-journal.net  # @pipelinejournal #pipelinejournal

6 Pipeline Technology Journal - 3/2024 Chairman Dr. Michael Beller Director, Global Market Strategy ROSEN Europe Members Editorial Board Adrian Lim Global Management Consultant INTECSEA Ana Nunez Anton EU Chemicals Pipeline Manager Shell Asle Venas Director Charge Energy AS Prof. Dr. Jürgen Schmidt Excecutive Director CSE Center of Safety Excellence Dr. Khalid A. Al-Jabr Reliability Engineering Specialist Saudi Aramco Mahmoud A. Hakim Head of Discipline Pipeline Engineering ADNOC Group Dr. Marion Erdelen-Peppler Secretary General EPRG Max Wedekind Managing Director DENSO Group Germany Dr. Mike Kirkwood Director, Integrity Engineering Solutions T.D. Williamson Mohd Nazmi bin Mohd Ali Napiah Custodian/Head/Group Technical Authority PETRONAS Steffen Paeper Independent Pipeline Professional www.pipeline-journal.net ptj@eitep.de puBlishEr EITEP, Euro Institute for Information and Technology Transfer GmbH Marie-Jahn-Straße 20 30177 Hannover, Germany Tel: +49 511 90992-10 URL: www.eitep.de issn e-ISSN: 2196-4300 p-ISSN: 2751-1189 usEd Copyright MatErial P. 8-9, 13, 16 © 2023 Ralph Thiele / EITEP Managing Board Dennis Fandrich & Marian Ritter Register Court: Amtsgericht Hannover Company Registration Number: HRB 56648 Value Added Tax Identification Number DE 182833034 Editor in ChiEf Dennis Fandrich E-Mail: d.fandrich@eitep.de Tel: +49 511 90992-22 tErMs of puBliCation Four times a year Editorial ManagEMEnt Marian Ritter E-Mail: m.ritter@eitep.de Tel: +49 511 90992-15 Constantin Schreiber E-Mail: c.schreiber@eitep.de Tel: +49 511 90992-20 Editorial staff Mark Iden Daniel Onyango

8 Pipeline Technology Journal - 3/2024

10 Pipeline Technology Journal - 3/2024 Winner Entries of the 2024 PHOTO CONTEST more information at www.pipeline-conference.com/photo-contest

12 Pipeline Technology Journal - 3/2024 Interview with YPI Early Achievement Award winner Toon De Bruyne How does it feel to receive such recognition from your peers in the pipeline industry? • It was a true honor to receive this recognition and to have the opportunity to say a few words on stage dur- ing the social gathering at the PTC. It is pleasant to see that the PTC and YPI want to sup- port young professionals in the industry and motivate them to aim even higher. Could you tell us about your background and how you became involved in the pipeline industry? I’m a Belgian Pipeliner and started working in the pipe- line industry in 2014 at the Belgian construction com- pany Denys directly when I received my civil engineer- ing degree. I did not know anything about the pipeline industry back then but I had to opportunity to work with several experienced coworkers who learned me everything on the job. I worked on several pipeline construction projects in Belgium, The Netherlands and Germany in different roles as site manager – pro- ject engineer and project manager. Since 3 years I’m working as project manager at Pipelink. Following the master in pipeline technology was really important, it gave me a complete vision of the industry next to the construction projects I was working on. • Working in Belgium-The Netherlands an Germany gave me a new, broader perspective on pipelines in Europe. Can you share any notable projects or initia- tives you've worked on that have had a signif- icant impact on the pipeline industry? • Pipeliner: first as a board member and currently as chair. Pipeliner is the foundation responsible for the Master in sciences in Pipeline Technology and a more professional course the so called ‘Beroepsopleiding’. With Pipeliner we want to help solve the war on talent for the pipeline in- dustry. We will try to give the pipeline industry a place in the programs of the general education and universities. • Working on facilitating the energy transition at Pipelink I’m now 33 years old, married and have two young chil- dren of 2 and 4 years old. In your experience, what are some of the key challenges that the pipeline industry faces today? Given your current role as a Projectmanager at Pipelink NV, could you discuss significant milestones that have led you to where you are right now in your career? • The Bad atmosphere around pipelines in the gen- eral public. It is important that everybody in the in- dustry talks positive about our industry when talk- ing about the job with friends and family. • Going to the jobfaire on my university where I got told about Pipelines, unfortunately a world noth- ing was told about during my school career. • The war on talent, in both blue and white collar jobs company’s are having difficulties to find the necessary people to achieve the ambitious goals for the energy transition.

14 Pipeline Technology Journal - 3/2024 Interview with YPI Emerging Young Pipeline Professional Award winner Nikolaos Makrakis Winning this Award is a significant achievement. Can you share with us how you felt when you re- ceived the news and what it means to you? I remember the day I received the news like it was yesterday! But first, let me start by sharing a short story. I was anx- iously awaiting the award results, so I emailed to ask when they would be announced. Two weeks after the official an- nouncement date, I still hadn't received any updates. Thus, disappointed as I thought I would not win the Award, one morning, I checked the spam folder and came across an email congratulating me for winning the Award. I was completely shocked and overwhelmed by so many emotions. The first thing that came to my mind was pure joy and gratitude. I immediately shared the news with my supervisors and my family, who sup- ported me throughout the process. Winning this Award means so much to me since it actu- ally confirms that my hard work, dedication, and passion are being recognized by experts. This achievement is a reminder to keep pushing myself towards excellence in everything I do, and never give up on my dreams. Could you provide an overview of your work or research focus and the potential impact it can have on the pipeline industry? I specialize, both scientifically and professionally, in Structural and Geotechnical Earthquake Engineering and Geoinformatics Engineering. Since 2018, I have been focusing on geohazard assessment and seismic design of energy lifelines, such as cables and high-pres- sure gas pipelines. Currently, I am a PhD student fo- cusing on Earthquake Engineering and Infrastructure Design, with emphasis on the optimal design of life- lines. My main aim is to improve the design of safe, functional and resilient lifelines and the whole deci- sion-making process of optimal lifeline routing sub- jected to geohazards, other hazards and multi-hazards. Apart from the scientific contribution to the interna- tional literature, I expect my research effort to con- tribute also to more practical aspects of lifeline geo- technics, seismic design and optimum route selection, thus being highly beneficial for energy companies and the pipeline industry. Having said that, I would like to thank my PhD super- visor, Dr Yiannis Tsompanakis, Professor in the School of Chemical and Environmental Engineering of the Technical University of Crete, Greece, and Head of Computational Dynamics & Energy (CODEN) Research Group. I really appreciate the trust he has placed in me and his continuous support. With his valuable guid- ance, the whole group produces high-quality research. What motivates and inspires you to continue pursuing a career in research and academia? Pursuing a career in research and academia generously provides the opportunity to engage with complex and challenging problems, think critically, and keep learn- ing and improving my skills and expertise. I am moti- vated by my curiosity to think and explore hidden things and therefore, to keep delving deeper and deeper into uncovering new knowledge. In addition, I am always passionate about conducting innovative research that not only contributes to the advancement of my research field but also inspires future generations of researchers. What are the key challenges you have faced in your research journey so far, and how have you managed to overcome them? I have encountered many challenges throughout my research journey so far. One big hurdle is dealing

these hobbies help me stay motivated and energized in both my personal and professional life. They provide me with pleasure, relaxation and they constitute an outlet for stress relief, allowing me to step away from the pressures of the workplace and release tension in a healthy way. 16 Pipeline Technology Journal - 3/2024 Pursuing a PhD is like a sine wave, with lots of ups and downs. The key is to stay focused and committed even during tough periods; i.e., at the downs of the sine wave, in order to achieve personal excellence and reach your goals. To do this, the most important thing is to take care of your physical, mental, and emotional well-being and keep a balance between work and per- sonal life. Apart from your professional pursuits, what are some of your hobbies or interests that bring you joy and help you maintain a healthy work-life balance? Apart from my professional pursuits, I am a health and fitness enthusiast, regularly attending the gym to maintain physical well-being and discipline. In ad- dition, one of my favorite activities is going for long walks and exploring beautiful places. Another thing I really enjoy is reading self-help books for personal growth, aiming to expand my knowledge and keep my mind engaged outside of work-related tasks. Overall, From left to right: Erik Cornelissen, Nikolaos Makrakis & Kate Stratogianni (© 2024 Ralph Thiele / EITEP)

18 Pipeline Technology Journal - 3/2024 ptj Insights Insights Well-known industry experts share their experience, insights and opinions on pipeline related topics Bats, Bees, Snakes, Octopuses, and Pigs! M. Kirkwood > T.D. Williamson Abstract In Professor Hopkins’ previous ptj Insights, the focus was on pipeline defects. In this ptj Insights, we will focus on anomalies. The word “anomaly” applies here since we will look at inspection de- vices that infer as-yet unconfirmed defects. An “anomaly” deviates from what is standard, normal, or expected. The word “defect” is only used when the anomaly has been confirmed as an imperfection.

20 Pipeline Technology Journal - 3/2024 ptj Insights hertz (Hz) detectable by the human ear. Ultrasonic ILI tools operate between 400 kHz and 25 MHz. only detect one or two types of defects. They remained blind to other anomalies and had not mastered the “art of looking”. These tools served a valuable purpose, but each could In 2019, my colleagues and I wrote a paper for ptc en- titled “The Art of Looking: An In-Line Inspection Perspective,” [7] which was inspired by Alexandra Horowitz [8], a specialist in cognitive science who researched the question: What is like to be a dog? In her book “On Looking: A Walkers Guide to the Art of Observation,” she explores seeing without seeing through 11 walks with different subject matter experts in her native New York - Figure 3. She uses the eyes of these experts to see different things given their “selec- tive enhancement,” or seeing what is important and discarding peripheral data. Each of the “walkers” en- hances what they see with their specialist’s eye. For example, a geologist sees more than 60 types of rock on the face and interior of the American Museum of Natural History. It would take a geologist to see the schist, gneiss, quartz and garnet in a building -- but what has he missed with this focused expertise? Possibly the Pantone colours of the window frames, the architectural signs of Greek revival, art deco, and even brutalism? The need for many senses makes animals better equipped to find things such as food, shelter, com- panionship, etc. The same analogy can be made in the world of pipeline inspection. Because the bat’s great echolation lets it operate in the dark, its sense of sight is not so good, and it tends to hunt at night. Similarly, while ultrasonic ILI tools are great in liquids or within a slug, they don’t do well in gas or even liquefied gas. As the saying goes, “horses for courses.” A while back, there was a lot of talk around how sen- sors were getting smarter, computers faster, batteries longer lasting and everything getting so much smaller that it could be possible to put several sensors on a sin- gle tool to look for every perceivable defect type and measure it. The concept of the colloquially termed “Swiss Army” tool [9] was bandied around the indus- try [10]. Was it developed? Well, nearly! The limiting factor tends to be volume. The smaller the diameter, the longer the tool — which becomes a practical limitation Figure 2: Wheel Tapper [4] Figure 3: On Looking: A Walkers Guide to the art of Observation - Horowitz [8]

22 Pipeline Technology Journal - 3/2024 ptj Insights • High field axial magnetic flux leakage (MFL): Detects volumetric metal loss, mill anomalies, and extra metal and has a strength in detecting wide features. • Low field axial magnetic flux leakage (LFM): LFM identifies magnetic permeability changes in the steel microstructure due to mechanical working and/or heating /cooling. • Helical/spiral magnetic flux leakage SMFL): Provides inspection of the longitudinal pipe axis, including weld seams, and detection of other longitudinally oriented anomalies. • XYZ mapping: Provides high resolution pipe centre- line trajectory. As this tool is based on the physics of magnetism (A- MFL, S-MFL and LFM), the type of weld and pipe body defects are mainly focused on those that have volume. Although some cracking presents itself magnetically, close fitting cracks need another technology such as UTCD or EMAT. Trying to cram all this technology onto one tool, as Keith Grimes of British Gas posited, “invariably raises the question as to who would genuinely wish to hire such a complex beast.” As Grimes states quite categor- ically, there is a cost implication -- not just in running the tool, but also for on-costs such as data analysis, the risk of damage and refurbishment and the unthinka- ble of getting stuck or damaged beyond repair. In Professor Horowitz’s - on looking world, this would be like walking a city block with five uniquely skilled subject matter experts! As an example, here are a series of images taken from an MDS run. 3. Case Study As I mentioned, some sensors overlap and some com- plement. For a picture of how the MDS tool can be de- ployed against a set of specified anomalies [11], we can draw a rather complex Venn diagram [12] - Figure 5. Figure 7 through Figure 11 show an example of the MDS datasets. Starting with Figure 6, the high resolution caliper (or DEF ) highlights significant indentation presenting INSPECT STABLE THREATS Coating and Lamination Anomalies Mill Anomalies Coating Disbondment Mid-wall Lamination Surface Breaking Lamination Hard Spots Lack of Fusion Slag Inclusion Construction-weld Anomalies Arc Strike Cold Weld Hook Crack Seam Variations Construction Anomalies Buckle Close Metal Objects Gouges and Grinding Expansions/Deformities Ovality Pipeline Curvature Re-rounded Dents Plain/Small Dents Wrinkles/Wrinkle Bends TIME INDEPENDENT THREATS Geological-force Anomalies Bending Strain and Residual Stress Ground Movement Washout and Erosion †As defined by B31.8S/INGAA Though not essential to detect this anomaly, the inclusion of this technology enhances identification and characterization. M F L L F M S M F L D E F E M A T X Y Z INTERACTIVE PIPELINE THREATS Interactive threats are the coincidence of two or more threats in a pipe segment, the result of which is more damaging than either of the individual threats themselves.† Stress Corrosion Cracking (SCC) Selective Seam Weld Corrosion (SSWC) Mechanical Damage MATERIAL VERIFICATION Pipe Joint Classification TIME DEPENDENT THREATS Metal Loss Anomalies Pinholes Pitting Corrosion General Corrosion Complex Corrosion General Wall Thinning Girth Weld Metal Loss Spiral Weld Metal Loss Zero Wall Environmentally-assisted Corrosion Anomalies Microbial Induced Corrosion Narrow Axial External Corrosion (NAEC) Crack Anomalies Axial Crack Circumferential Crack Girth Weld Crack Longitudinal Seam Weld Crack Spiral Seam Weld Crack Environmentally-assisted Crack Anomalies Fatigue Crack Hydrogen Induced Cracking Figure 5: Venn Diagram for ILI Against Defects Defined in POF [11]

24 Pipeline Technology Journal - 3/2024 ptj Insights In this case, we would have excavated the defect purely on the strength of just one or two of the data sets. However, additional data sets do help us determine whether the dent was larger upon impact, whether the metal loss is a gouge, and the material hardening be- cause of the impact and metal flow. These datasets all align and allow us to make this call, which is a massive step forward from the simple Kaliper tool of the 1970s. However, I left one super animal until last: Octopuses boast a sophisticated array of senses. They possess keen vision, sensitive touch facilitated by suckers on their arms, discerning taste, and a sharp sense of smell. Furthermore, their ability to detect alterations in light polarization enhances their camouflage and commu- nication strategies. Remarkably, octopuses exhibit an advanced sense of proprioception, enabling them to perceive the positions of their limbs without visual cues. Recent studies propose the presence of a distrib- uted nervous system within their bodies, suggesting a unique form of intelligence or awareness that enriches their understanding of the environment. Octopuses have been around for 296 million years (Carboniferous period); ILI development only spans some 50 years, so we have a long way to get as good as an octopus! 4. Final comments There are many ILI tool types now available. Thus, most defects can be detected, sized, and characterized to a given specification. Using the wrong tool because it is convenient reminds me of the idiom “buy cheap, Author Dr. Mike Kirkwood T.D. Williamson Director, Integrity Engineering Solutions Mike.Kirkwood@tdwilliamson.com buy twice.” In the pipeline world, there are wider im- plications of getting it wrong. When considering in- spection needs, operators need to consider the balance of costs and return on investment as well as the need to meet regulatory rulings. In choosing the right tool or tools, I refer back to the analogy of “horses for courses.” In this simple idiom, there are thoroughbreds bred to run fast for short pe- riods (racing) horses bred for elegance and gymnastics (dressage), for getting over fences and hedges (show jumping), and for running fast with amazing stamina (endurance), to name a few. I will certainly not enter any of my champion dressage Friesians in the next Grand National or Kentucky Derby. So, make sure you assess the threats you are looking for and select the right tool or tools for the job. “VLIP VAN GRIETJE N” – RIP References 1. Reddit, "Culvert Snakes," 2016. [Online]. Available: https://www.reddit.com/r/snakes/comment- s/4y40xk/culvert_snakes/. [Accessed Aug 2024]. 2. Reddit, "In a while…," 2021. [Online]. Available: https://www.reddit. com/r/funny/comments/o87yk8/in_a_while/. [Accessed Aug 2024]. 3. Bio Explorer, "Top 11 Animals With Super Sensors," 2023. [Online]. Available: https://www.bioexplorer.net/ani- mals-with-best-sensors.html. [Accessed Aug 2024]. 4. BBVA, "The Champions of the 5 Senses in the Animal World," 2022. [Online]. [Accessed Aug 2024]. 5. PPSA, "History of the first Kaliper (ILI) tool," 2023. [Online]. Available: https://ppsa-online.com/newsletter/2023-06/12. [Accessed Aug 2024]. 6. BG Technology, "History of the Engineering Research Station 1964 -1993," BG Technology, 1995. 7. D. Burden, M. Maldonado and M. Kirkwood, "The Art of Looking:An In-line Inspection Perspective," in Pipeline Technology Conference (ptc), Berlin, 2019. 8. A. Horowitz, On Looking: A Walker's Guide to the Art of Obseration, Vols. ISBN-10-1439191263/ISBN-13:978-1439191262, Scribner,, 2014. 9. Victorinox, "Swiss Army Knives from Victorinox," Aug 2024. [Online]. Available: https://www.victorinox.com/en-GB/ Products/Swiss-Army-Knives/c/SAK/. [Accessed Aug 2024]. 10. K. Grimes, "The Changing Role of Inspection," in International Pipeline Conference, Calagry, 1998. 11. Pipeline Operator Forum, "Specifications and requirements for in- line inspection of pipelines," Pipeline Operator Forum (POF), 2016. 12. M. Kirkwood, C. Harris and P. Barbosa, "The New 2016 Pipeline Operators Forum (Pof) Specification; A Vendors Experience," in 13th Pipeline Technology Conference, Berlin, Germany, 12-14 March 2018.

26 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Hazard Based Protection of Gas Infrastructure Facilities against Cyber-Physical Attacks M. Bächle, J. Schmidt > CSE - Engineering Center of Safety Excellence GmbH Abstract The rapid growth in digitalization and automation results in indus- trial plants increasingly interconnected through IT (Information Technology) and OT (Operational Technology) networks. While this interconnectedness offers significant operational advantages, it also makes plants vulnerable to cyber-physical attacks. Such attacks can lead to major accidents like fires or explosions. Currently, sce- narios resulting from cyber-physical attacks are inadequately con- sidered in process hazard analyses, such as HAZOP studies. To pro- tect plants against these threats, a comprehensive combined safety and security analysis is required. Therefore, the novel Safety-Cyber- Security-Evaluation (sCSE) methodology is presented, which builds upon existing HAZOP studies. The sCSE methodology identifies po- tential safety-relevant scenarios resulting from cyber-physical at- tacks, determines potential attack vectors, and derives appropriate security countermeasures. Finally, the security countermeasures are prioritized for implementation.

28 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY By converting the HAZOP study into a matrix format, the following scenarios resulting from a cyber-physi- cal attack can be identified: (1) Attacks on safety instru- mented systems, leading to the non-performance of one or more safety instrumented systems. (2) Simultaneous triggering of various safety scenarios that are covered by the same safety countermeasure. Safety countermeas- ures are sized under the assumption of a single primary failure and can be overloaded by the simultaneous trig- gering of multiple safety scenarios. (3) Simultaneous triggering of multiple non-safety-relevant scenarios that, in combination, can cause a safety-relevant sce- nario and may not be covered by adequate safety coun- termeasures. (4) Attacks on the availability of essential functions according to IEC-TR63069. Since the matrices are directly based on the columns of the HAZOP table, the conversion can be automated. 3. Identification of Potential Cyber Threats In the next step, the potential cyber threats that trigger the safety-relevant scenarios are identified. Through this analysis, vulnerabilities and their potential impact on the physical process are determined at component level. To identify possible security threats, the Chemical Security Guideword method (CSGM) is used, which is de- rived from the STRIDE framework (Khan, McLaughlin, Laverty, & Sezer, 2017). Guidewords, that represent po- tential cyber threats, are applied to the components of the OT network. The following guidewords are used: that are exploited by the threats. An example for the Chemical Security Guideword Method is shown in Figure 2. In the shown example, the guideword “Manipulation” is applied to a temperature transmitter with a Bluetooth interface, whereby the communication via the Bluetooth interface is manipulated due to a Man-in-the-Middle at- tack. For example, the vulnerability CVE-2023-24023 ac- cording to the NVD (National Vulnerability Database) can be exploited for this purpose. This process determines potential attack vectors (A), which are then converted into the matrix format in the third step of the sCSE-Methodology, as shown in the orange matrices in Figure 1. The matrices highlight possible attack vectors against components. Additionally, the orange matrices can help to determine if an attack vector can simultane- ously trigger multiple safety-relevant scenarios, poten- tially overloading safety countermeasures. The attack vectors can be generically created for various standard components, allowing this step to be largely automated. T Component Temperature Transmitter with Bluetooth Interface Guideword / Threat Manipulation Manipulation of the Bluetooth Communication due to a Man-in-the-Middle Attack • Delay: Unavailability of information due to a delay of data on a communication channel Vulnerability Vulnerability in a Bluetooth Device, e.g. the vulnerability CVE-2023-24023 from NVD (National Vulnerability Database) • Denial of Service: Blocking of a critical service which leads to an unavailability of the service • Trigger: An unauthenticated execution or activa- tion of a software function on the target component • Manipulation: Malicious modification of existing information to change the behaviour of the target component • Resequencing: Maliciously manipulated bus de- vice modifies the safety message sequence After applying the guidewords (i.e. cyber threats) onto the OT components, possible vulnerabilities are determined Figure 2: Applying the CSGM to a temperature transmitter with a Bluetooth interface. 4. Prevention of Vulnerability Exploitation To prevent the exploitation of vulnerabilities by cyber threats, appropriate security countermeasures must be implemented. Potential security countermeasures are derived from IEC 62443, the BSI IT-Grundschutz Compendium, and other regulations. Both IEC 62443 and the BSI IT-Grundschutz Compendium define dif- ferent levels of protection for each security counter- measures. The selection of an appropriate level of protection is based on the risk associated with the

30 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY New Generation of AI Techniques Applied to Third Party Interference and Leakage Detection on Pipelines A. P. Gomes, M. Marino, M. Biagini, F. Chiappa > Enivibes Abstract This paper presents a pipeline monitoring system designed to detect, locate, and classify leakages and Third-Party Interference (TPI) inci- dents along a pipeline right-of-way using Vibroacoustic Technology. The system is ideal for retrofitting existing pipelines and focuses on real-time asset monitoring to detect activities such as excavation or impacts that could cause damage. Vibroacoustic waves generated by anomalies, i.e., TPIs or leakages, propagate for several kilometers inside the pipeline. Strategically placed pressure sensors and accelerometers along the pipeline cap- ture the data, that are then transmitted to computational units with advanced algorithms for noise reduction, event detection, and localization. The system employs machine learning and deep learning tech- niques, including convolutional neural networks, to classify TPI events, enhancing detection accuracy and minimizing false alarms. This innovative AI-driven approach offers a robust solu- tion for maintaining pipeline integrity with potential to become a key tool in pipeline asset protection.

32 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY vibroacoustic sensors showing correlation above a pre-defined threshold as a candidate contributing to the TPI alarm, irrespective of the nature of the noise source. To address this challenge, an evolution of the computational system is proposed, with the primary goal of recognizing the nature of the noise source to enhance the efficiency of the VT TPI system during the detection phase. The key concept involves classifying leak and TPI events based on their vibroacoustic signatures to identify the nature of events responsible for anomalies, i.e., events that differ from background noise. For example, a man- ual excavation produces a vibroacoustic response char- acterized by sequences of impulses resulting from shovel and/or pickaxe impacts on the ground. In contrast, the signature of a civil structure experiencing vibrational stress due to rush hour traffic generates wide-band ran- dom noise while drilling for irrigation water produces a narrow band of regular noise, and so forth. Leakages give rise to vibroacoustic transients upon initiation, variation, or extinction, along with a con- tinuous stationary jet noise throughout their dura- tion. In contrast to TPI vibroacoustic signatures, leak signals exhibit such distinct characteristics that an initial filter segregates the data related to leaks and TPI. This segregated data is then directed to each VT detection module, ensuring that distinct information is provided for leak and TPI detection. The challenge addressed in this work involves cat- egorizing excavations and background noise of TPI vibroacoustic noise through a classification system. The most effective approach is to train an AI engine to recognize these types of vibroacoustic signals and integrate it into the current TPI software module. This enhanced system has the potential to become a versatile and powerful tool for ensuring the integ- rity of pipeline assets, filling a gap currently absent from the landscape of pipeline integrity monitoring applications. 2. Third Party Interference (TPI): Understand the System approaching the pipeline, excavation operations, and tapping preparation. The VT leak detection system is able to detect some tap- ping preparations and the subsequent leakages. In con- trast, the VT TPI system technology is capable of detect- ing excavation activities, a crucial aspect for effective prevention for buried pipelines. It is fundamental to emphasize that the time-domain and spectral signa- tures of these signals differ significantly from events caused daily activities, e.g., passage of trains, cars, etc. These distinctive features are crucial in discerning false alarms from real ones, a concept that becomes relevant when discussing convolutional neural networks (CNN). Acoustic pressure data enables both detection and lo- calization, while the vibrational component, ever-pres- ent on the pipeline shell, poses challenges in detection, requiring sensitive equipment and advanced signal processing techniques. The TPI physical propagation model centers on the mechanical energy generated by ground vibrations, which is transferred to the soil, only then resulting in an elastic wave transmitted to the pipeline fluid and shell. This wave undergoes an acoustic conversion, creating a signal that propagates several kilometers within the pipeline. There is an exponential relationship between the dis- tance from the noise source to the fluid and the trans- ferred energy quantity. In instances of excavation, me- chanical energy is transferred first to the soil, then to the pipe shell, and finally to the fluid, following an ex- ponential model. The maximum energy transfer occurs when excavation is performed on the top of the pipeline. If the energy is strong enough to create vibroacoustic waves that reach at least two sensor blocks, localization is achieved with high accuracy (less than 25m) by means of cross correlation techniques. However, if the vibroacous- tic waves reach only one station, precise localization is not feasible, but it is still possible to issue an alarm to no- tify the pipeline operator of an anomalous event near the sensor block. The occurrence of TPI activities, whether or not they re- sult in illicit tapping events, does not follow a universal rule, but typically involves a sequence of steps, including 2.1 False Alarms Issue Given the diverse nature of the signals generated and the extensive network of pipelines spanning numer- ous kilometers across varied environments, the VT

34 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Figure 3: Vibroacoustic data obtained during TPI tests (top) and the corresponding spectrogram (bottom). 4. Test Campaign This paragraph outlines the details of the test cam- paigns conducted to gather vibroacoustic data, aimed at comprehensively studying signal propagation be- yond the pipeline and the associated energy conver- sion phenomenon occurring at the pipeline shell. This method enables the identification of channel propaga- tion characteristics critical for understanding the sys- tem behavior. This comprehensive test campaign incorporates tai- lored experiments designed to simulate authentic TPI events, thereby contributing to the calibration of the system. The tests performed include impacts on the pipeline shell, mechanical and manual excavation (Figure 4), calibrated weight-drop on the ground. The calibrated weight-drop test (Figure 5) is non-inva- sive and facilitates the estimation of the energy trans- ference from the ground to the pipeline, ensuring a re- peatable calibration process. This device administers a constant amount of energy to the ground through a calibrated weight falling from a standardized height, ensuring precise calibration of the system. Direct impacts on the pipeline shell were executed to illustrate variations in amplitude recorded by the sen- sors. This comparison highlights distinctions between noise sources originating directly from activities con- ducted on the pipeline shell and those initiated on the ground, relying on energy transmission to reach the pipeline shell.

36 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY the prevailing method for weight updates - to adjust the weights across the entire network. The loss function evolution during the training pro- cess (Figure 6) reveals a gradual decline over train- ing epochs, indicating the increasing proficiency of the model in minimizing discrepancies between predictions and actual values. Simultaneously, the accuracy graph (Figure 7), defined as the ratio between the number of correct predictions with respect of the total number of samples, depicts a consistent upward trend, affirming the ability of the model to make precise predictions. This upward trajectory in accuracy not only showcases the overall classification power, but also provides a dynamic view of the learning process and the model adaptation to the dataset. Delving further into the accuracy metric, we find that it not only serves as a global performance indicator, but also enables a nuanced under- standing of individual class distinctions. Moreover, both the loss function and accuracy are il- lustrated for both the training and validation datasets. This enables us to determine the optimal number of epochs and implement an early stopping algorithm to prevent overfitting. Analyzing accuracy per class provides valuable insights into the model strengths and potential areas for improvement across different categories. The confusion matrix (Figure 8), with its visual rep- resentation of true positive, true negative, false positive, and false negative predictions, becomes instrumental in dissecting the intricacies of the model classification outcomes. Identifying areas of misclassification is cru- cial for refining the model architecture and enhancing its robustness across diverse data instances. In essence, these results collectively contribute to a ho- listic evaluation of CNN’s classification performance. They not only affirm its effectiveness in capturing overarching patterns but also provide a granular per- spective, allowing for targeted improvements. These findings serve as a valuable guide for iteratively refin- ing the model, ensuring its adaptability and reliability in handling various real-world scenarios. Based on this analysis, it can be affirmed that the train- ing process has exhibited remarkable stability, yield- ing an impressive accuracy of 99.63% on the test data- set. This high accuracy has, in turn, contributed to the exceptionally robust performance of the VT TPI sys- tem. It excels not only in the precise classification of excavation events but also in mitigating false alarms arising from various noise sources that collectively contribute to the overall background noise. Figure 6: Iterative loss function. The gradual decrease in training data and the consistently low values on validation data indicate the growing proficiency of the model.

38 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY References 1. Dalmazzone, G. M., De Lorenzo, G., Giunta G., 2016, System and method for the continuous detection of impacts on pipelines for the trans- portation of fluids, particularly suitable for underwater pipelines, ENI S.p.A, Patent US9267648B2 (2016), EP2483656B1 (2017). 2. Giunta, G., Bernasconi, G., 2017a, Method and system for continuous remote monitoring of the integrity of pressu- rized pipelines and properties of the fluids transported, Patent EP2936106B1 (2017), US10401254B2 (2019). 3. Giunta, G., Bernasconi, G., 2017b, Method and system for the remote detection of the position of a pig de- vice inside a pressurized pipeline, EP2935969B1 (2017), US9897243B2 (2018). 4. Giunta, G., Bernasconi, G., Del Giudice, S. 2017c, Method and system for the continuous remote tracking of a pig de- vice and detection of anomalies inside a pressurized pipeline, EP294485700B1 (2017), US10132823B2 (2018). 5. Marino, M., Chiappa, F., and Giunta G. 2019. Anticipating bunkering events: notable cases evidence using Vibroacoustic Leak Detection Technology to detect precursors. Paper presented at the 14th Pipeline Technology Conference, Berlin, Germany. 6. Marino, M., Chiappa, F., and Giunta, G. 2020. Versatile Technology for Leak Detection, Third Party Interference and Integrity Assessment Applications: Vibroacoustics. Pipeline Technology Journal. 7. Marino, M., Chiappa, F., and Giunta, G. 2020. Pipeline integrity assessment applications by using vibroacous- tic technology. Paper presented at the 15th Pipeline Technology Conference, Berlin, Germany. 8. Marino, M., Chiappa, F., Giunta, G. 2021. A vibroacoustic integrated technology for the detection of a wide spectrum of il- legal activities. Paper presented at the 16th Pipeline Technology Conference, Berlin, Germany. 9. Marino, M., Del Giudice, S., Chiappa, F., Giunta, G. 2022. Applications of Vibroacoustic Technology to support pipeline assets re-use, integ- rity management and energy transition projects. Paper presented at the 17th Pipeline Technology Conference, Berlin, Germany. 10. Marino, M., Gomes, A.P., Del Giudice, S., Giunta, G. 2023. Integration of multiple Leak Detection Technologies into a single Advanced Leak Detection System. Paper presented at the 18th Pipeline Technology Conference, Berlin, Germany. 11. Marino, M., Del Giudice, S., Chiappa, F., Giunta, G. 2022. Advanced Leak Detection Applications for Pipeline Integrity Management using Vibroacoustic Technology. Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference. 12. Marino, M., Gomes, A.P., Reynaud J., Ekpikie, O., Giunta, G. 2023. Detection of Leakage and Illicit Tapping by Means of Vibroacoustic Technology in a Challenging Regional Scenario. Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference. 13. Biagini, M., Gomes, A.P., Chiappa, F. 2023. Toward AI Data-Driven Pipeline Monitoring Systems. Pipeline Technology Journal. Authors Ana Paula Gomes Enivibes Business Development Manager ana.gomes@enivibes.com Marco Marino Enivibes Managing Director marco.marino@enivibes.com Massimiliano Biagini Enivibes Team Leader Signal Processing and AI Division massimiliano.biagini@enivibes.com Fabio Chiappa Enivibes R&D Manager fabio.chiappa@enivibes.com

40 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY From Pipelines to Home Heating: The Digital Transformation of Natural Gas Distribution S. Şenol1, S. Bilim1, Ö.F. Güner1, M.H. Çevik2 > 1İGDAŞ, 2İstanbul Technical University Abstract The distribution of natural gas through Istanbul's pipelines requires the control of temperature, pressure, draft, consumption, and composition to securely reach 16 million people. The digitalization journey begins at the gas takeover points and extends to the combi boilers of residents. SCADA is integrated into all regional and central metering stations, facilitating seamless communication and generating extensive data on gas behavior. Smart meters monitor natural gas consumption and velocity, collecting precise data from households for detailed analyses. By using this vast data for future predictions, management and optimi- zation of the gas distribution network, AI could usher in a new era of data-driven technologies in natural gas distribution. From the pipe- lines to residents, the journey of natural gas is meticulously tracked, enhancing operational efficiency and paving the way for more intelli- gent systems in gas distribution management.

42 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Figure 2: SCADA Control Room Data is received instantly from RMS/A stations and every five minutes from other instruments. This data is used for various purposes, including reading, report- ing, and archiving measurements and alarms, and re- motely stopping gas supply for security. Through Remote Terminal Units (RTU) at pressure reduction and metering stations, crucial signals like inlet-out- let pressures, consumption data, and valve positions are transmitted to SCADA. Monitoring this integrated system generates alarms for immediate issues such as natural disasters, fires, malfunctions, and gas leaks, which are then handled by relevant units. Continuous service is provided based on information from the ALO 153 Solution Center and the 187 Natural Gas Emergency Line. This entire system is managed by the SCADA control room, as shown in Figure [2]. Before the implementation of SCADA, Maintenance and Network Superintendencies manually collected data from instruments at regular intervals throughout the day, with no alarm systems in place. Issues like gas outages and filter blockages were detected via the 187 emergency line or during periodic inspections. Now, with remote reading and automatic alarm transmis- sion, superintendencies only check instruments when anomalies occur, leading to significant improvements in operational processes and cost reductions. SCADA data informs various functions: the Survey and Project Directorate uses it for investment planning simula- tions, the Gas Procurement Superintendency makes gas purchase decisions, and the Commercial Services Directorate remotely bills certain customer stations. The Cathodic Protection Superintendency analyzes its system, Maintenance Superintendencies enhance op- erations, the Disaster Management Superintendency remotely resets SI sensors at 832 Regional Regulators, RMS Operations Superintendencies monitor RMS/A data via local SCADA systems, and the Internal Installation Directorate benefits from customer Qmin and Qmax data.

44 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY The Research and Development department benefits from SCADA data to monitor gas conditions and compositions, allowing them to identify problems and potential solutions. The system enables us to chart trends in gas behavior at each main and regional regulating station. Representative data for gas flow between february and april-2024 is indicated at Figure [3]. One intance is the ability to visualize and track the accumulation of condensate, particularly at low alloca- tion points within Istanbul. Condensate formation occurs due to sudden changes in gas temperature and pressure, leading to the accumulation of heavy hydrocarbons (C6+) within the gas stream. SCADA is integrated into the conden- sate accumulation regional regulation station, allowing us to track and evaluate the possibility of condensate occur- rence with respect to various parameters such as tempera- ture, pressure, and flow as shown at Figure [4]. Another example is the issue of odor within the gas composition. Odor fade is a phenomenon that occurs due to absorption on the surface of the pipelines or chemical reactions involving the contents of natural gas. TBM/THT is expected to be 70%/30% per 10 mg/ sm³ concentration within the natural gas flow stream. Fluctuations in their concentrations are monitored at seven different points within Istanbul and two of them is indicated at Figure [5]. When the concentration falls below the threshold, an alarm system on the SCADA screen alerts the maintenance department. Both of these examples illustrate the role of SCADA in ensuring the safety of natural gas during its journey to homes. Following the meticulous monitoring and con- trol at the pipeline level, the next crucial step in digital- ization involves the integration of smart meters with the SCADA system. This integration not only enhances real-time data acquisition but also ensures a seamless and secure delivery of natural gas to homes. Through this combined approach, both the broader network and individual household consumption can be effec- tively managed. 3. Artificial Intelligence and Data Analytics in SCADA Integration Effective management of natural gas distribution net- works is crucial for energy security, supply-demand balance, and sustainability. Artificial intelligence of- fers new opportunities for optimizing these networks, playing an increasingly important role in demand forecasting, anomaly detection, energy efficiency, and distribution optimization. Natural gas demand forecasting with artificial intel- ligence can be applied for various periods and these forecasts can cover short-term (hourly or daily) and long-term (monthly or annual) periods. Forecasts can be performed using various machine learning and sta- tistical methods such as linear regression (LR), ran- dom forest regression (RFR), artificial neural networks (ANN) and support vector regression (SVR). For data sets such as historical natural gas consumption data, temperature forecasts, seasonal variables, population information and natural gas prices can form the basis of these forecasts. Natural gas demand forecasts can be diversified depending on the data sets and method- ology used and can be applied by selecting the most ap- propriate methods in line with the needs. Such mod- els have the potential to increase efficiency in energy management and logistics processes. In addition, a study found a high negative correlation of -0.89 be- tween natural gas demand and outdoor temperature, indicating that gas demand increases as tempera- tures drop (Hribar et al., 2018). This finding suggests that weather forecasts can play a critical role in natu- ral gas demand forecasts. Artificial intelligence mod- els have significant potential to more accurately pre- dict future weather conditions by processing complex weather data. These forecasts can be integrated into natural gas demand projections, increasing efficiency in energy management. Datasets used to detect anomalies in natural gas dis- tribution include data from various sources, such as pipeline pressure data, flow rate, temperature, con- sumption patterns, and weather data, as well as time series data. This data is used to train artificial intelli- gence models. Datasets are usually created by simulat- ing normal and abnormal situations, and models are trained with this data. Anomalies are detected by the models, while deviations from normal and unexpected changes are analyzed (Zheng et al., 2022). In this pro- cess, machine learning algorithms learn past data patterns and identify deviations from these patterns. Thus, anomalies such as leaks, pressure drops, and un- usual consumption increases in pipeline systems can be detected quickly and accurately. These methods in- crease safety in natural gas pipeline systems and min- imize economic losses and environmental damage.

46 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY habits, system performance, and potential fraud activ- ities. Additional security measures, such as access con- trols and audit logs, are implemented to protect data integrity and confidentiality. AI and ML platforms play a critical role in data collec- tion from IoT portals. These platforms provide a layer for data processing, visualization, and querying. The AI-based analytics engine analyzes consumption pat- terns, detects fraud activities, and helps users reduce energy usage. It also provides data for decision sup- port systems, performs predictive maintenance, and optimizes network performance. This platform offers a standardized interface for data access and analysis from IoT portals, facilitating project participants' abil- ity to interact with and analyze data. 4.2 Creation and Use of Different Consumption Profiles Smart meters collect data on natural gas consumption on a daily, weekly, and monthly basis. This data is ana- lyzed in a central system and categorized into segments such as low, medium, and high consumption users. This segmentation allows for understanding and opti- mizing energy consumption behaviors. Consumption profiles help in developing energy efficiency strategies and creating customized billing plans. They are also used to predict future energy demand and for planning purposes. Users can analyze and improve their habits through a platform that allows them to track their con- sumption. These processes are crucial for optimizing energy consumption behaviors and using energy re- sources more efficiently. For this reason, data collected in the pilot project has been segmented into various categories: User Consumption Data (daily, weekly, and monthly con- sumption, peak and low usage periods, seasonal var- iations), Geographical Data (urban vs. rural consump- tion, regional habits and infrastructure), Demographic Data (age, income, household size, lifestyle for per- sonalized services), Sensor and Device Data (real-time data from smart meters, meter status, anomalies), and Environmental Data (weather, temperature changes affecting consumption forecasts). These segments help create and utilize different consumption profiles, illustrating their significant impact. 4.3 Detection of Gas Leaks, Unauthorized Usage, or Abnormal Consumption Situations One of the biggest challenges in gas distribution sys- tems is detecting gas leaks, unauthorized usage, and abnormal consumption situations. As a gas distribu- tion company serving 16 million customers, we utilize smart meters and AI-based platforms to address these issues. Smart meters continuously monitor and ana- lyze gas consumption and flow rates in real-time. This allows for the immediate detection of any anomalies and rapid intervention. These systems significantly contribute to enhancing safety and efficiency, improv- ing operational performance. Smart meters are equipped with sensors that continu- ously monitor gas consumption and microprocessors that process this data. These sensors measure the flow rate, pressure, and total consumption of the gas, trans- mitting the data to a central system. Data analysis is used to detect possible fraudulent activities and abnor- mal consumption situations in the system. For instance, an unexpected increase or decrease in gas consumption could be an indicator of fraud or unauthorized usage. Gas leaks can pose serious safety hazards. Smart meter data can detect leaks by monitoring sudden drops in consumption patterns. Data from the sensors, which monitor gas flow and pressure, trigger alarms in the event of sudden and unexpected changes. These alarms detect anomalies in the system and notify the central system. When a gas leak or abnormal con- sumption situation is detected, the central system quickly intervenes and takes the necessary safety measures. The collected data is continuously analyzed by the central system. Sensor data monitors gas flow, pressure, and consumption, providing instant alarms for any anomalies. These alarms are promptly commu- nicated to central system operators and users. 4.4 Pilot Project and Advanced Data Analytics Techniques Currently, we are conducting a pilot project involving approximately 2,500 smart meters across three dif- ferent regions in Istanbul. In these trials, we use NB- IoT and LoRaWAN technologies for data transmis- sion. Additionally, we are testing 5G network slicing technology to create flexible and efficient network segments for various applications. This pilot project aims to investigate how smart meters and advanced

48 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY 6. Acknowledgment The authors would like to extend their gratitude to Paşa Ari and his team from the İGDAŞ SCADA depart- ment for their assistance and support. References 1. Hribar, R., Potočnik, P., Šilc, J., & Papa, G. (2018). A comparison of mo- dels for forecasting the residential natural gas demand of an urban area. Energy, 167, 511–522. https://doi.org/10.1016/j.energy.2018.10.175 2. Saboo, S. (2024). Optimizing Gas Pipeline Operations with Machine Learning: A Case Study of A North American Energy Company. Society of Petroleum Engineers - SPE Conference at Oman Petroleum and Energy Show, OPES 2024. https://doi.org/10.2118/218564-MS 3. Zheng, J., Wang, C., Liang, Y., Liao, Q., Li, Z., & Wang, B. (2022). Deeppipe: A deep-learning method for anomaly de- tection of multi-product pipelines. Energy, 259(July), 125025. https://doi.org/10.1016/j.energy.2022.125025 AuthorS Sinem Şenol İGDAŞ Specialist (technical) sinem.senol@igdas.istanbul Sonay Bilim İGDAŞ R&D Engineer(industrial) sonay.bilim@igdas.istanbul Ömer Faruk Güner İGDAŞ R&D Engineer (mechanical) omerfaruk.guner@igdas.istanbul Muharrem Hilmi Çevik İstanbul Technical University – Petroleum and Natural Gas Engineering Research Asistant cevikmuh@itu.edu.tr

50 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY How to select the right Leak Detection Methods to cover Legal and Operational Requirements m. Ihring, D. Vogt > KROHNE Solutions Abstract Leak detection systems are a crucial part in pipeline safety. Unfortunately, general knowledge about these systems is still limited. Due to advantages and limitations of single leak detection technologies the selection process can be difficult – especially when regulation and different operating scenarios have to be considered. Single methods might work well for some standards, regu- lations and specific operating scenarios while not covering others. The paper shows how different leak detection methods can be used to fulfil the requirements of regulations and standards such as German TRFL (Technical Rules for Pipelines) or API 1130. The different requirements and special fea- tures of these applications for leak detection are described. Furthermore, it also describes how different leak detection technologies can be applied so that pipeline operation during changing operating scenarios such as steady-state, transient or shut-in operation is monitored allowing leak detection during all operating conditions. This is shown by presenting a real project example. Finally, a systematic approach for the leak detection method selection is pre- sented considering application, operational and legal requirements.

52 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY TRFL. These included the steady-state operation, the transient operation, standstill operation, completely or partially blocked lines and the detection of gradual leaks. In total the pipeline was operated in 12 different operating scenarios. The regulatory and operational requirements for the detection of leaks were fulfilled by using a mul- ti-method approach. This was achieved by implement- ing a horizontal combination of methods according to the requirements of TRFL. On top of that a vertical combination of methods using model calculations and leak signature analysis with pattern recognition was implemented to improve the sensitivity of the system and avoid false alarms. Due to this approach, it is pos- sible to achieve detection times in minutes. This approach does not only improve sensitivity and robustness, but also allows better individualisation and optimisation to the applications. Furthermore, it allows individual redundancy concepts and an optimal adaption to the operator environment due to the selec- tion of the best matching methods for the application. In the application the methods E-RTTM, E-NPW, sta- tistical line balance, tightness monitoring using a pressure-temperature-method, gradient intersection method and extended negative pressure wave method were combined in one common overall system. E-RTTM was implemented as one of two continuously operating technical processes that detects leaks in steady-state operation. It also covers the requirements for detecting leaks in transient operation. Figure 2: Horizontal and vertical combination of pipeline leak detection methods

54 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Table 1: Overview of the regulatory requirements and implemented leak detection modules Figure 3: Operating scenario 1 of the distribution network and overview of leak detection methods for the individual pipeline sections

56 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY The Checklist is a management approach which sup- ports the operator in continuous improvement of their leak detection performance. This approach is also re- flected in API 1175 and is part of a leak detection strat- egy. Within the leak detection audit, the installed methods are investigated based on current KPIs (Key Performance Indicators) against the operator’s desired performance, industry best practice and Best Available Technology (BAT). Based on the investigation and in- formation of the pipeline operation, instrumentation and communication, recommendations are given on how to achieve the desired KPIs. In the Company Readiness check, the alarm manage- ment and procedures are analysed with the overall goal of identifying opportunities for improvement of real leak cases. When there is a leak, it is crucial that the company and its personnel know how to react and initi- ate the right procedures in a fast manner and still avoid making false decisions. This is where the Company Readiness check supports the operator. Necessary train- ing needs for the control room staff and the implemen- tation of work procedures will be identified and solu- tions are given to close the identified gaps. The leak detection audit is a service to check all leak detection areas of a pipeline or a pipeline network of an oper- ator to ensure the functionality in all required areas of leak detection. It is therefore the most compre- hensive test program available for leak detection and covers the physical state of the system, performance of the system, compliance with regulations including API, 49 CFR 195, CSA Z662 and TRFL and the readiness of an organisation to deal with emergency. At the end of the audit, the operator receives a detailed report of all the tests performed including an overview of the extent to which all requirements have been met. The report also includes recommendations depending on how critical points can be improved and a certificate for the direct proof for the leak detection capabilities. 4. Summary Different leak detection methods can be used to ful- fil the requirements of regulations and standards such as German TRFL (Technical Rules for Pipelines) or API 1130. KROHNE has successfully proven this by using multi-method approaches in a variety of applications. This approach also allows the detection of leaks during all operating scenarios of a pipeline including chang- ing operating scenarios such as steady-state, transient or shut-in operation as well as accurate leak localisa- tion. By using pipeline leak detection audits, a system- atic approach for the leak detection method selection is available that considers application, operational and legal requirements to support operators and engineer- ing companies in finding the right leak detection tech- nologies and philosophy. Figure 5: Pipeline leak detection audit report and certificate sample

58 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Comparative Assessment of Levelised Cost of Different Hydrogen Transportation Technologies M. Aneke, N. Curson, C. Low > Penspen Abstract Hydrogen, a vital energy vector, is widely accepted as essential for de- carbonising the global energy system. Hydrogen has a variety of roles to play in a low-carbon economy. Hydrogen can replace fossil fuels as a zero-carbon feedstock in chemical and fuel production [2]. It can also be used to extend the scope of climate transition to sectors that the electrification of energy cannot reach, as well as long-distance transport and heat-intensive industries such as steelmaking [1], and it can be used as storage, making it an enabler in most national decar- bonisation roadmaps [3]. In a future hydrogen economy, the vision is for hydrogen to be trans- ported across borders from countries with a high excess of renewa- ble energy that can be used to generate green hydrogen to countries without access to renewables. In the UK, the Scottish Government’s hydrogen Policy Statement aims to deliver 5GW of renewable and low-carbon hydrogen production by 2030 and 25 GW by 2045. The European Commission has also established a global ambition, target- ing 10 million tons of hydrogen to be imported by 2030. In Europe, the Port of Rotterdam is an established energy hub, already imports 13% of Europe’s energy, and has ambitions to become the hydrogen hub of Europe. A challenge in exporting hydrogen is choosing the best means of transportation. In this paper, different technologies for transport- ing hydrogen from Aberdeen Harbour to the Port of Rotterdam were assessed and compared using the levelized cost as a reference.

60 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Table 1: Common Process Parameters for the Different Options S e a t R o u t e D i s t a n c e = 5 2 4 n a u t i c a l m i l e s Figure 1: Sea Route from Aberdeen Harbour to Port of Rotterdam (yellow represents the shipping route) [5] 7 2 3 k m Figure 3: Pipeline route between Aberdeen Harbour and Port of Rotterdam Figure 2: Road Route from Aberdeen Harbour to Port of Rotterdam 3. Process Description and Modelling of the Different Hydrogen Conversion Technologies 3.1 Hydrogen Liquefaction Process Figure 4 shows the process diagram of the hydrogen liquefaction system considered in this study. The liq- uefaction technology is based on a mixed refrigerant pre-cooling cycle and a hydrogen Claude cycle, as de- scribed in [5]. The process is modelled using Aspen Hysys® simulation software using process parameters presented in [5]. 3.2 LOHC Production and Dehydrogenation Process The LOHC is assumed to be methylcyclohexane (MCH) which is produced via exothermic catalytic hydrogena- tion of toluene based on the chemical equation shown below.

62 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Figure 5: LOHC (MCH) Production Process & MCH Dehydrogenation Process The simplified process flow diagram of the LOHC (MCH) dehydrogenation process is shown in Figure 5 [7]. For this assessment, toluene is assumed to be pur- chased as feedstock for the MCH production. a pressure of 150 bar and temperature range of 270 – 450°C. The rate equation and kinetic parameters are presented below. 3.3 Green Ammonia Synthesis and Cracking Process Figure 6 [10] shows the process flow diagram of the green ammonia synthesis process. The process uses nitrogen generated from the cryogenic air separation unit with hydrogen from the electrolysis process to produce ammonia. where, The ammonia synthesis process is modelled in Aspen Hysys® using a plug flow reactor operating at kf and kr = the rate constant for the forward and reverse reactions, respectively Figure 6: Green Ammonia Synthesis Process

64 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY 4.1 Levelised Cost of Hydrogen Transport by Road/Ship using Tube Trailers For transportation by road, the hydrogen will first be compressed and stored in tube trailers before being transported by road to the destination. The transpor- tation time for delivery by truck or ship can be calcu- lated based on the equation below. For the case of transport by ship, the annual capital cost (CC) is the sum of the cost associated with the hy- drogen conversion plant, pump, ship, and storage ves- sels, considering the annuity factors (AF) that might be different: Hence for transporting the hydrogen using a LOHC, where, D = distance to the location of delivery v = average speed of the truck LT = loading time at the filling station UT = unloading time The number of round trips NRT per year follows from the number of hours per year the truck is utilised and the roundtrip time. where, U = utilisation time of the truck/ship over a year (it is as- sumed the only time the truck is not utilised is during loading and unloading) For transporting the hydrogen as liquid Ammonia, For transporting the hydrogen as liquid hydrogen The annual operating cost (OPEX) consists of com- pressor electricity costs, fuel costs, labour costs for the driver, and annual maintenance costs. where, Cele = Annual electricity cost for operating the plant (compressor, pumps etc) Cutility = Annual utility cost (cooling water) Pf = truck/ship fuel cost (assumed to be diesel-powered) The quantity of hydrogen to be transported by the truck or ship is given as Cf = truck/ship fuel consumption where, K = Capacity of the ship or truck. For the case of road transport using tube trailers, the annual capital cost (CC) is the sum of the cost associ- ated with compressor, tractor, trailer, and storage ves- sels (tube trailers), considering the annuity factors (AF) that might be different: Cd = hourly wages (driver, ship captain and ship crew members) COM = annual maintenance cost (assumed to be 3% CAPEX for all cases) For the shipping option, the assumed fuel consump- tion of the ship for the lightest commodity (liquid hy- drogen) is corrected to include the influence of weight on fuel consumption of ship. The correction factor is calculated using the following equation.

66 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY

68 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Table 3: Summary of Input Parameters for the different transport options In terms of the quantity of hydrogen transported per annum, the pipeline transport system shows the highest throughput of 719,563,280 kg, followed by Ammonia of 311,106,390 kg, then liquid hydrogen of 310,073,616 kg, LOHC of 182,085,737 kg and tube trailer of 147,593 kg. 6. Conclusion This study presents the levelised cost of hydrogen transport, including gaseous hydrogen using tube trailers, gaseous hydrogen using a pipeline, liquid am- monia using a ship, liquid organic hydrogen carrier using a ship, and liquid hydrogen using a ship. Unlike most published literature based on generic CAPEX and OPEX data from publications, the work presented in this study was carried out through detailed modelling of the individual processes involved in the transport process. By taking this approach, we can accurately evaluate the OPEX of the different options (in terms of electricity and water consumption) that have the most impact on levelised cost estimates. In terms of evaluation, the study doesn’t consider the cost of carbon emissions in burning fuel (diesel), em- bodied carbon, and developments in air separation and cracking technology, which could reduce the cost of ammonia transportation. These are all subject to further study. References 1. Cheng, Wenting and Lee, Sora (2022), How Green Are the National Hydrogen Strategies, Sustainability, 14, 1930. 2. IRENA (2019), International Renewable Energy Agency, Hydrogen: A Renewable Energy Perspective; available at: https://www. irena.org/-/media/Files/IRENA/Agency/Publication/2019/ Sep/IRENA_Hydrogen_2019.pdf (accessed on 18/03/2024). 3. IRENA (2020), International Renewable Energy Agency, Green Hydrogen: A Guide to Policy Making; available at: https://www.irena. org/-/media/Files/IRENA/Agency/Publication/2020/Nov/IRENA_ Green_hydrogen_policy_2020.pdf (accessed on 18/03/2024) 4. GlobalData (2023) Hydrogen Transition Outlook and Trends Q1 2023, April 2023, ; available at: https://www. globaldata.com/ (accessed on 08/06/2023) 5. Berstad et. al., (2020), Dissecting the exergy balance of a hydrogen liquefier: Analysis of a scaled-up Claude hydrogen liquefier with mixed refrigerant pre-cooling, International Journal of Hydrogen Energy. 6. Aberdeen Harbour to Port of Rotterdam: 524 nautical miles, avai- lable at: http://ports.com/sea-route/#/?a=106&b=3037&c=A- berdeen%20Harbour,%20United%20Kingdom&d=Port%20 of%20Rotterdam,%20Netherlands, (accessed on 19/03/2024) 7. Maleki, H. et. al., (2021), Kinetic assessment of H2 production from NH3 decomposition over CoCwAlO catalyst in a microreactor: Experiments and CFD modelling, Chemical Engineering Journal, vol 411. 8. Keane, M. A and Patterson, P. M. (1999), The role of hydrogen par- tial pressure in the gas phase hydrogenation of aromatics over supported nickel, Ind. Eng. Chem. Res. 1999, 38, 1295 – 1305. 9. Marlin T. E, (1967), The Catalytic Dehydrogenation of Methylcyclohexane at 720F, A thesis submitted to the School of Engineering, University of Dayton, in Partial Fulfilment of the Requirements for the Degree of Master of Science in Engineering.

70 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Circular Economy Concept for Aboveground Storage Tanks - Change In Service B. Narasannagari, Y. Alhannoush, Dr. K. Al-Jabr > Saudi Aramco Abstract Along with extending the life cycle of products, the oil and gas sector has recently implemented the circular economy. Its goals are to increase longevity, manage waste more effectively, and provide an optimal design that makes it simpler to repair, reuse, or remanufacture outdated prod- ucts. In order to decrease waste and increase the lifespan of items, many materials and products may be repaired, altered, or reused. Asset Integrity Management is a key element of operational excellence along with optimizing the efficiency while maintaining the safety and environment. Storage tanks have been widely used in industries, par- ticularly in oil refineries, petrochemical plants, storage terminals and others to store a multitude of different products. An important ob- jective in supply distribution is to meet user demands on time and in a cost-effective manner. Changing the service of an existing Above Storage Tank (AST) is a common strategy in ensuring a continuous flow of product which can contribute significantly to improved efficiencies and higher lifetime earnings. Change in service of existing ASTs requires careful evaluation and as- sessment based on several factors affecting the tanks design, inspection, maintenance and operations. This is a multi-discipline evaluation look- ing into different aspects of the tank design and functionality. The paper mainly refers to “Aboveground Storage Tanks Change in Service” through covering a sample procedure based on recognized standards and best practices. This paper will address the effective techniques of changing service through listing all the input parameters and factors along with the description of each item that might affect the change in service

72 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Roofs (IFR) in existing fixed cone or dome roof tanks, which will have potential impact on the liq- uid levels, internals, venting requirements and the foundation loads. 3. Fluid corrosivity: If the new service fluid is more corrosive than the existing service fluid, corrosion study shall determine the mitigative actions like adding corrosion allowance, recalculating cathodic protection or applying suitable internal coating. 4. Design pressure: Increase in design pressure (in- ternal &/or external) of the tanks for new service will impact the tank shell thicknesses and foun- dation loads. This may also potentially require as- sessment of the tank for applicability of API 650 Annex F & V and subsequent alterations to the tank roof and roof-to-shell junction. 5. Design temperature: Increase in design tempera- ture of the tanks for new service may impact the tank shell thicknesses and the foundation loads. This might also potentially require assessment of the tank for applicability of API 650 Annex M. 6. Liquid levels: Tank users have to be flexible with liq- uid levels as it may not be possible to maintain the existing liquid levels. As indicated above under specific gravity, maximum allowable liquid lev- els may be reduced due to increase in the specific gravity. For volatile fluids, when IFR is added the liquid levels have to be reduced to accommodate the IFR. 7. Material of construction (MOC): Existing AST MOC shall be verified for suitability to new service. The physical and chemical properties of the existing materials shall be compatible with the new service and operating conditions. 8. Process internals: Liquid inlet distributors may have to be added when IFR is added to the exist- ing tanks. Other tank internals like floating suc- tion, floating skimmers or stilling wells may have to be added based on the type and criticality of the new service. 9. Tank accessories: Tank accessories like the require- ment of instrumentation nozzles, mixers, heaters, etc., shall be reviewed by the process engineer. 10. Filling and discharge rates: Any increase in the fill- ing and discharge rates may impact the tank inlet and outlet nozzle sizes. Tank process nozzle sizes verification will be required to be performed by the process engineer based on the new filling and dis- charge rate changes. Tank nozzle modifications shall be performed in accordance with API-653. 11. Venting requirements: Any increase in the filling and discharge rates or higher flammability of the new process fluid may impact the tank venting re- quirements. Thus, the existing venting capacities shall be verified for suitability for new service by process engineer in consultation with the vents manufacturer. 12. Peripheral seals: Compatibility of the seals for new service shall be verified. The secondary seal fab- rics check shall be performed when the tanks are cleaned. Hydrotest the roof drain as a precaution. 13. Cathodic protection (CP): Integrity of the existing cathodic protection systems shall be verified prior to reusing the existing CP system. In addition, the existing internal CP system shall be redesigned if the corrosivity of the new service is higher than the existing. 14. Fire protection (FP): Based on the flammability of the new service, FP requirements of the tank and the area around the tank shall be considered while planning of retaining or repairing the tank. 15. Coating requirements: Based on the corrosivity of the new service, the internal coating systems shall be assessed by the corrosion or coating engineer. 16. Insulation requirements: Based on the flammabil- ity and design temperature of the new service, the tank shall be assessed if a heat conservation insu- lation is required. 17. Foundation loading: Increase in specific gravity with- out changes to the liquid levels will have impact on the foundation loadings. Adding IFR in a fixed roof tank will also have impact on the foundation loadings. Foundation loading assessment has to be

74 Pipeline Technology Journal - 3/2024 RESEARCH • DEVELOPMENT • TECHNOLOGY Comprehensive inspections of existing AST shall be performed by a certified API 653 authorized inspector. After that, the Tank Engineering Specialist shall decide any additional non-destructive testing or hydrotest re- quirement based on the mechanical integrity check. AST settlement survey should be also evaluated in ac- cordance with the provisions of API 653, Annex B if hy- drotest is performed. After completion of the AST change in service assess- ment and put into operation, a new internal inspection plan has to developed for the new service. Maintaining accurate and up-to-date documenta- tion is essential for tracking AST design changes. It is imperative to update the AST datasheets, Vendor As- Built drawings, tank accessories Original Equipment Manufacturer (OEM) manuals, inspection records, re- pair & maintenance records for future reference. As a summary, Figure 1 describes the required assess- ment and its steps and processes that should be fol- lowed for any change in service for aboveground stor- age tanks. For our case study that was done to change the service of existing fixed dome roof Heavy Diesel Oil (HDO) Tank to Fire Water Tank, the results of the assessment were analyzed and recommended to switch the service for the tank as summarized in the Appendix-1. Table 1: Appendix – 1

76 Pipeline Technology Journal - 3/2024 ask the experts Ask the Experts Digitalization & Security Q1) Where do you see the main possibilities of AI for pipelines in the future? corrosion or external damage, and alert operators to take preventive measures. Ove Heitmann Hansen: I see immense potential for AI, Machine Learning and Hybrid models in the pipe- line industry’s future. The power lies in interoperabil- ity and utilization of complex systems, but you need to get the foundation right with structured and qualified data. The main possibilities cover: I. Predictive Maintenance: AI can analyse data from sensors to predict when parts of the pipeline might fail, allowing for proactive maintenance, faster re- placements, and reduced downtime. II. New infrastructure: Optimal route selection of new pipelines utilizing geospatial analysis of local and global datasets. III. Data analysis: Process vast amounts of data to provide insights and trends that can inform de- cision-making and strategic planning. AI can as- sess complex datasets faster and more effectively, enhance data quality and accuracy, and fill in data gaps. IV. Leak detection: AI and advanced algorithms can detect anomalies in pressure and flow data, iden- tifying leaks more quickly and accurately than tra- ditional methods. V. Optimization of operations: AI can optimize the flow of materials through pipelines, adjusting pa- rameters in real time to maximize efficiency and reduce costs. VI. Safety enhancements: Simulating “perfect storm” failure scenarios across a pipeline network and connected datasets by identifying pre-markers that will lead to those scenarios. AI can moni- tor pipelines for potential safety hazards, such as VII. Environmental monitoring: AI can help monitor en- vironmental impacts, ensure compliance with reg- ulations, and minimize ecological damage. VIII. Automation: AI can automate routine tasks, freeing up human operators to focus on more com- plex issues and create training material for new engineers as well as Q2) How can AI algorithms be utilized to pre- dict and prevent potential pipeline failures or dis- ruptions, and what are the best practices for im- plementing these solutions? Ove Heitmann Hansen: Digitalization and AI capabili- ties depend on trust and quality of the data. The data quality assurance and certification can range from triv- ial rules to complex evaluations and verifications based on reasoning mechanisms, Machine Learning, and AI, emphasizing data quality, confidentiality, integrity and availability. To predict and prevent potential pipeline failures or disruptions, we need to establish the follow- ing capability levels: I. Descriptive Level: The current state is described and visualised by cleaning the data and making it acces- sible to understand what is happening. This could, for example, be a 3D model. II. Diagnostic Level: By adding sensor information to the descriptive model, decisions about the current state or condition can be made by identifying cor- relations in data to understand why it is happening. III. Predictive Level: By adding intelligence and analyt- ics to the diagnostic model, one can start to predict

78 Pipeline Technology Journal - 3/2024 ask the experts account for these differences to ensure proper pres- sure management and flow control. III. Leak Detection: Hydrogen molecules are smaller and more prone to leakage. Simulation models must be adapted to detect and predict potential leak sce- narios specific to hydrogen. IV. Blending Scenarios: Many transitions will involve blending hydrogen with natural gas. Models need to simulate various blending ratios and their impacts on the system. V. Safety and Risk Assessment: Given hydrogen's high flammability, safety simulations are crucial for risk assessment and mitigation planning. The main challenge lies in the accuracy of these models, given the limited real-world data on large-scale hydrogen pipeline operations. At DNV, we're developing and vali- dating these models through a combination of labora- tory testing and pilot projects, leveraging our extensive experience in natural gas and hydrogen systems. Over- coming these challenges requires a multidisciplinary approach, combining materials science, fluid dynamics, and risk assessment expertise. Q5) How are digital twins being used to en- hance predictive analytics capabilities in pipe- line monitoring, and what are the main techno- logical and data challenges to be addressed? Ove Heitmann Hansen: Network demand, especially for natural gas, can fluctuate greatly not only day-to-day, but hour-by-hour. Internal pressure associated with high demand and increased flow places higher stress on the pipe, which brings it closer to its failure state. Overlay- ing and aligning network analysis/hydraulic modelling, maintenance records, operational history, integrity as- sessments, corrosion control data (e.g. CP performance, CIS and VG surveys, coupon sampling), and other com- plementary datasets, including externally available data, is already occurring to help operators pinpoint po- tential risk along a pipeline. The next step is providing an engineer or analyst with the ability to leverage these aligned datasets (i.e. “Digital Twins) daily, empowering them to work smarter and faster; however, this relies on implementing a robust enterprise data platform with a well-planned architecture. The future will be an inter- face/application that allows those engineers to “drag and drop” data from various datasets to build their own AI/ML models that will enable them to make critical, thoughtful, and tactical decisions while removing the more tedious data cleansing tasks that many are bur- dened with today. The two biggest challenges are: I. Digital Architecture and Data Platform: Implement- ing a Digital Data Platform that integrates various information models, ensures interoperability, and provides shared services across the company is fun- damental, as well as hosting, validating, contextual- izing, securing, and managing structural data. II. Data Alignment and Relationships: Understanding how data is aligned is a critical first step to ensuring that a digital twin is represented correctly. The rela- tionship between data and the asset it is associated with can sometimes be complex, and a reflective ap- proach may be required on a case-by-case basis (e.g., time-series SCADA data, which is a point associated with segments of pipe within a pressure network). Hence, an assurance process of digital twins for Da- ta-driven verifications and predictive analytics needs to comply with technology qualification, capability and data quality assessments, and verifications of all simu- lation models and AI-enabled systems. Q6) What strategies can pipeline operators em- ploy to ensure the interoperability of various digital systems and platforms across their operations? Ove Heitmann Hansen: Ensuring interoperability across diverse digital systems is crucial for maximiz- ing the benefits of digitalization in pipeline opera- tions. Steps that can be taken to ensure interopera- bility between digital systems and the data they own and manage are as follows: I. Unique identification across digital systems: As- sets have one unique identifier that is utilized in all digital systems (i.e., one asset does not have different names/IDs in different digital systems). For example, a mainline valve is identified in the Work Management System, in the SCADA system, and GIS. II. Data Standardization and Protocols: Deploying Data Standards that establish common data for- mats and standards across the organization en- sures that different systems can easily share and understand data. Minimizing free-form text fields and utilizing domains whenever possible

80 Pipeline Technology Journal - 3/2024 ptj Young Pipeliner Constantin Schreiber Managing Editor EITEP Institute A Spotlight on the Future: Young Professionals Shaping the Pipeline Industry As Editor of the Pipeline Technology Journal I am proud to announce a new column in the ptj. In our Pipeline People segment on the ptj website we already have in- terviewed young professionals in the pipeline industry. But with the ptj Young Pipeliner column we add another way of supporting the new generation of people who have decided to work in this field and give them a opportunity to reach out to pipeline professionals all over the world. The pipeline industry, a cornerstone of global infrastructure, is un- dergoing a transformation. As we look to the future, it’s clear that innovation, sustainability, and technological advancements will be key drivers of change. However, the most critical factor in ensuring the industry’s continued success is its people. In this column, we aim to shine a spotlight on the young professionals who are joining the pipeline industry and shaping its future. These young engineers, technicians, and other specialists bring fresh perspectives, new ideas, and a deep understanding of emerg- ing technologies. They are the innovators who will develop the next generation of systems and programs, the problem-solvers who will find creative solutions to complex challenges, and the leaders who will guide the industry into a sustainable future. In each installment of this column, we will feature papers of young pipeliners who are making a contribution to the pipeline industry. Ultimately, the goal of this column is to be a spotlight that highlights the ideas and innovations coming from this new generation of pipe- line professionals. Sincerely Yours, Constantin Schreiber Managing Editor EITEP Institute

82 Pipeline Technology Journal - 3/2024 ptj Young Pipeliner 1. Introduction In-line inspection (ILI) tools can measure a range of different defect types with a high degree of accuracy especially considering the harsh environments that the tools operate in. However, there are occasions when the specification of the tool can not be met due to the operating conditions, feature specific morphol- ogy and other factors. It is essential therefore to un- derstand if the tool has performed within its specifi- cation on a run by run basis. In the US this is a legal requirement under PHMSA, but is seen as best practice in most other countries around the world. Validation of crack like defects is a manual process which is significantly influenced by the procedure uti- lised and the skill and experience of the in-field opera- tor. Significant variability can therefore be seen in the tolerances of these inspections which has significant implications on the validation of the ILI tool. The introduction of Hydrogen into the gas networks will reduce the critical flaw size of crack-like indica- tions due to the potential embrittlement of the mate- rial. The inclusion of additional uncertainty in the ILI tolerance could be detrimental to the integrity of the pipeline network. If in-field verification of an unknown quality is used to validate the ILI for hydrogen conversion pipelines, the additional uncertainty that can be attributed to crack sizing of unknow quality can be significant enough to cause failure in a number of features in cross country pipelines. 2. ILI Validation Despite advances in technology, ILI validation is still a very manual process and the tolerances associated with each feature are significantly influenced by user skill and experience as well as technology selected. User variance is most significant in crack sizing where there are a number of different technologies that have the capability to size cracks all with pros and cons for various morphologies and combined feature types. However, independent user tolerance is rarely known in in-service inspections due to the variability and challenges with understanding system performance. Therefore conservative tolerances should be adopted, like the ones seen in BS 7910. These are fine to use for individual integrity assessments as the conservative nature of the measurement means that safe repair op- tions will be utilised. However applying these conserv- ative tolerances to ILI validation measurements puts a significant amount of uncertainty in the ILI meas- urement. A ±3 mm tolerance for shear wave UT is rec- ommended by BS 7190 [1], which at a 1 mm detection threshold would make most features unacceptable in cross country hydrogen pipeline. In order to reduce the tolerance of the in-field inspec- tion, a blind trial is required to understand specific in- spector tolerance using the chosen inspection system. Figure 1: Potential tolerances of various feature types 3. Hydrogen Effect on Validation The EPRG review on integrity assessment methods for hydrogen conversion [2] discusses how the tolerable crack dimensions are affected by the introduction of hydrogen into the gas networks with various charpy toughness’s and are shown in Figure 2. Figure 2: Tolerable seam weld axial cracks for transmission pipelines

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Elevate your asset integrity with unmatched data accuracy and unparalleled expertise. Our unique synergy of advanced inspection systems, cutting-edge analytics and human expertise allows us to transform data into knowledge. Knowledge enables smarter decision- making and delivers a comprehensive understanding of asset safety, lifetime, and performance. www.rosen-group.com Unlock the Power of Data