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Papers

“It’s not enough to do your best; you must know what to do, and then do your best.” (W. Edwards Deming, Statistician 1900-1993) – Challenge accepted.

At ROSEN, we strive to enable asset operators to make the best possible integrity management decisions. Each time an inspection of any given asset takes place, an enormous amount of data accumulates. Taking this raw data and cleansing, interpreting and analyzing it allows us to transform data into information and information into knowledge. Knowledge enables smarter decision-making.

From February 17 to 20, 2020, at the George R. Brown Convention Center and the Marriott Marquis Hotel in Houston, TX, we will highlight a series of pipeline integrity solutions that enable operators to gain the knowledge needed to make the best-informed decisions.

Crack Management

Cracks threaten pipeline integrity. But not all cracks are the same. A variety of crack types such as fatigue cracks and environmental cracking as well as crack locations – including in the pipe body and in the complex geometry of girth welds and seam welds – all pose risks to a pipeline’s efficiency and safety.

The ROSEN pipeline crack management framework encourages a holistic approach to pipeline cracking. Our Inspection services identify a wide variety of crack formations with a very small physical footprint. They also find crack-like features such as manufacturing flaws.

The framework would not be complete without our integrity group, which has unrivaled experience in identifying likely flaws, selecting inspection system combinations, interpreting in-line inspection data, providing assessments and managing threats.

Learn more:
Pipeline Crack Management - Take Control of Cracks

Pipeline Material Verification

Where pipeline operators do not have adequate records to substantiate and validate the material properties of their pipeline, they will need to undertake further material properties verification efforts to determine or verify key attributes, including, but not limited to, the following:

Grade / SMYS
Seam type
Diameter
Wall thickness
Toughness

Where traceable, verifiable and complete (TVC) records are not available, key integrity decisions are full of uncertainty. Knowing the materials your pipelines are made of is critical for ensuring safe operation. To ensure safe, cost-efficient and code-compliant operation of a pipeline throughout its life, operators must understand their pipeline properties in order to accurately identify and address specific integrity threats.

Learn more:
Material & Pipe Properties - Take a Smart Look Into Your Pipe Wall

In-Field Validation Service

ROSEN is responding to the growing need for diagnostic services and to the latest changes in AP1163 by expanding its portfolio of on-site inspections and verification. Among others, the new requirements for pipeline operators include verifying in-line inspection (ILI) results by comparing them with field data.

Using the latest technologies and qualified personnel, ROSEN enables accurate on-site data acquisition and validation of pipeline characteristics such as deformations and anomalies, internal and external corrosion, and cracks as well as the identification of pipeline material properties. This approach provides an optimal basis for field verification and allows ROSEN to increase the integrity of the pipeline system while reducing the number of digs in order to avoid short- and long-term costs.

Additionally, a unique web-based platform enables one-to-one comparisons of complete data sets by achieving the highest degree of accuracy thus creating the optimal basis for the further development of sizing algorithms with artificial intelligence and machine learning.

In addition, we will be featuring our “Innovation Corner,” where our latest developments and strategies will be introduced.

NIMA - Elevating Safety

A holistic approach to integrity requires a reliable system of record and adaptable Asset Integrity Management (AIM) processes. We believe, what operators need is an accurate reflection of their individual integrity management process in a digital solution. NIMA is an intuitive and reliable framework comprised of a guide, a set of tools, and recourses that delivers data you need, in the way that you need it, to make better integrity management decisions. The resources include a platform, personnel, and training elements that are pieced together according to what you already have and the gaps you need to fill, your needs.

Learn more:
NIMA - Elevating Safety

Virtual–Dig Up

Virtual–Dig Up - Breaking the Boundaries

It is time to overcome the technical boundaries of traditional magnetic flux leakage (MFL) data evaluation and taking MFL technology to the next level. ROSEN is proud to present a revolutionary new technology, one that enhances the level of information drawn from data that is implicitly available in high-resolution MFL and collected during ILI runs. This new technology - only available from ROSEN - is called Deep Field Analyze and uses high-quality data from axial and circumferential MFL inspections to provide laser-like 3D profiles of a metal loss feature, visualizing the true shape of any corrosion or gouging even before a dig up. This truly unprecedented approach breaks the boundaries, taking us beyond boxing based on feature length and depth! Virtual–Dig Up is a new service offering built around Deep Field Analyze.

Benefits of the Virtual–Dig Up service offering:

True metal loss shape: highest confidence in data interpretation
Maintenance optimization: dig up prioritization and faster decision-making for future activities
Integrity confirmation: less conservative calculation of safe burst pressure

Learn more: Innovation at the Forefront

Ready for Hydrogen

Fit for the Future - Ready for Hydrogen

As the world moves towards a decarbonized future, global demand for fossil fuels continues to rise. In this context, renewable hydrogen will play an important role by reducing overall emissions along the entire value chain in the oil and gas industry. There are approximately 1,600 miles of hydrogen pipeline already in operation in the United States alone.¹ We must be ready for pipelines to efficiently and safely transport this medium while ensuring their safety throughout their lifecycle, just as we have in the past. Taking a holistic approach to pipeline integrity, ROSEN supports operators in converting existing gas infrastructure to be used for hydrogen transportation – working towards a decarbonized and sustainable future.

Learn more: Innovation at the Forefront

Reference
¹ Shell Deutschland Oil GmbH/Wuppertal Institut: Shell Hydrogen Study. Energy of the Future? Sustainable Mobility through Fuel Cells and H₂, 2017, p.26, https://www.shell.com/energy-and-innovation/new-energies/hydrogen/_jcr_content/par/keybenefits_150847174/link.stream/1496312627865/6a3564d61b9aff43e087972db5212be68d1fb2e8/shell-h2-study-new.pdf

Visit us at Booth #707 to discover more and speak directly to our subject-matter experts.

At the conference, our experts will give ten technical presentations on a diverse range of topics, including Virtual-Dig Up, Machine Learning and Material Property Verification. Furthermore, ROSEN will deliver two training courses and host the plenary opening session entitled “Beyond Compliance.”

Papers

Plenary opening session

9:00
Wednesday, February 19

Beyond Compliance ...

Jan Frowijn (ROSEN)

Abstract

Plenary opening session

It is clear that we need to invest in energy efficiency and renewables. At the same time, most predictions show that oil and natural gas are an important part of our energy future. In the U.S. oil and natural gas production is soaring and there is no credible way to transport oil and natural gas without pipelines. We think to believe that we do all we can to protect communities and the environment with safe pipeline operations: beyond compliance. Was it only just that simple. The energy debate raises deep controversies. For those in the industry it may often seem that regardless of improvements in integrity management practices and pipeline safety, public resistance to pipelines and anxieties of various kinds only seem to intensify. Knowledge and experience operate within various social frameworks, including the nature and degree of people's trust in scientific experts and authority. This talk gives an insight of theories of public opinion formation and change. Understanding the public’s concerns at a fundamental level is useful for all stakeholders and the pipeline industry at large in developing and communicating the pipeline narrative.

Paper 1

14:00
Wednesday, February 19

Calculation of a laser-scan-like 3D defect profile from conventional MFL Data

Johannes Palmer, Andrey Danilov (ROSEN Group)

Abstract

3D defect profile as input for more-accurate defect assessment and supplemental the safe pressure prediction. Reliable prediction of safe operating pressure is increasingly required in pipelines. Complex-shaped volumetric metal loss is a challenge in this regard...

Paper 1

3D defect profile as input for more-accurate defect assessment and supplemental the safe pressure prediction.

Reliable prediction of safe operating pressure is increasingly required in pipelines. Complex-shaped volumetric metal loss is a challenge in this regard. Methodological ILI restrictions and principal reporting simplification reduce the precision of ILI results and output tables.

Today, phenomenological MFL data parameterization is rearranging complex metal loss structures and often results in reduced accuracy. Nevertheless, the established maximum depth boxes do not necessarily prevent cases where MFL data interpretation is insufficiently conservative.

The presented groundbreaking MFL data evaluation technique directly calculates the accurate 3D metal loss geometry as an alternative to the currently practiced boxing. The resolution of the innovative result opens a new dimension for MFL. Auxiliary components of the typical MFL indirect interpretation method lose importance with this new system. Experience-based practices using human expertise, artificial intelligence or elaborate sizing models play a role still, but the conclusive accuracy of the calculated metal loss profile becomes significantly independent from the variability of these experience-based practices.

This technology enables new services for difficult-to-access areas, areas with complex corrosion, or instances in which a laser map cannot be obtained, resulting in a more accurate, reliable and detailed corrosion growth assessment. This paper will detail concrete case examples from blind tests with high-resolution laser maps and will compare the new approach with results from the traditional MFL evaluation. Performance and reliability analyses help rationalize this innovative technique and demonstrate the contribution to more reliable management of metal loss threats.

As part of describing this new evaluation technique, theoretical and practical advantages will be discussed of combining axial and transverse MFL measurements for detection and sizing of metal loss anomalies.

Paper 2

15:00
Wednesday, February 19

Machine Learning to Support Risk and Integrity Management

Christopher De Leon, Michael Smith (ROSEN Group)

Abstract

Paper 2

This presentation focuses on leveraging historical in-line inspection (ILI) data to better understand the likelihood of failure associated with pipelines that have not yet been inspected. This helps to support the prioritization of asset integrity assessments such as Direct Assessment (DA) or investments to modify pipelines to make them piggable. There is significant scope for enhancing this process compared to current practice.

Over the past 30 years huge volumes of ILI data have been collected, such that many uninspected pipelines can usually be compared with numerous similar inspected pipelines. This leads us naturally towards machine learning as an complementary monitoring solution for unpiggable, difficult to inspect, and low risk pipelines. Machine learning techniques help us to create accurate predictive models from relevant historical data.
These models can then be used to support practical integrity management decisions.

Using a pilot data warehouse containing ILI data for over 5,000 pipelines, we show how machine learning techniques can provide a route to understanding external corrosion behavior in uninspected pipelines.

Paper 3

16:30
Wednesday, February 19

Generation and monitoring of synthetic crack-like features in pipeline materials using cyclic pressure loading

Dr. Chris Alexander, Jon Rickert (ADV Integrity, Inc., Magnolia), Rhett Dotson, Felipe Freitas, Simon Slater, Christopher De Leon (ROSEN Group)

Abstract

Paper 3

Crack management has become a major focus for many gas and liquid transmission pipeline operators. Failures associated with crack-like features have been a concern for both operators and regulators. As a result, pipeline operators are excavating large numbers of features for not only in-line inspection validation purposes, but also to make repairs. Additionally, in-line inspection technologies have advanced significantly in recent years and are identifying an increasing number of features with greater levels of accuracy.

Because of high levels of conservatism associated today’s assessment methods, pipeline operators are spending a significant amount of capital excavating crack-like features. There is a need for improved assessment methods that integrates testing simulated / synthetic crack-like features. This paper will provide details on a study funded by ROSEN to systematically generate crack-like features in pipeline materials with the application of cyclic internal pressure loading. Synthetic crack-like features were generated using electronic discharge machining (EDM) to form notches in pipe materials. Initial stages of the program involved sectioning features to quantify crack growth levels. Once a systematic process had been validated, testing involved cyclic pressure fatigue to failure and burst testing. Programs such as the one presented in this paper are useful for both generating features in pipeline materials and also quantifying behavior considering cyclic pressure and burst loading.

Paper 4

17:00
Wednesday, February 19

Pipeline GIS and Mega Rule Part 1: Material Property Verification and the System of Record

Simon Slater (ROSEN Group)

Abstract

Paper 4

Following the introduction of the amended gas regulations, operators of gas transmission pipelines will be required to conduct a plethora of assessment and verification activities to achieve MAOP reconfirmation. This will require the collection, organization, and analysis of a staggering amount of data. The effective execution of these activates will require a structured, methodical, and repeatable process and to document any reconfirmation activities and results. This paper will provide an overview of the reconfirmation process, and how pipeline data systems can be used provide a platform to manage the data acquisition activities, the structure to support analysis of the acquired data, and verifying the results of this analysis within the System of Record (the pipeline GIS). Examples using real data will be presented that demonstrate the process of material properties verification, MAOP verification, and how Pipeline GIS Data Models (PODS 7) can be leveraged to store data through the reconfirmation process.

Paper 5

8:00
Thursday, February 20

Burst Testing of Pipes Containing Stress Corrosion Cracking

Simon Slater, Chris Davies (ROSEN Group), Dr. Chris Alexander, Chantz Denowh (ADV Integrity), Todd Post (Consumers Energy)

Abstract

Paper 5

Managing the assorted threats in pipelines is an evolving process. The inspection technologies, material testing methods and models used to assess feature severity improve over time. With respect to the assessment of crack-like features, the most commonly used approach is some form of analytical calculation using the inputs of feature, size, loading conditions and material properties. The inputs selected will almost certainly include some level of conservatism. In addition, there are many things embedded in our approach that tend to differ from what will be the case in “real-life”. The ability exists to supplement feature assessment with larger-scale testing of actual features removed from service. This enables a demonstration of what the actual burst pressure would be in a real-life scenario while helping to understand the failure mechanism and type.
The results from larger-scale tests can be used to bolster understanding and assist in making sound integrity decisions. They can be used in addition to the predicted burst pressures to deliver more representative results of the full material section under the same loading conditions as features would experience. Large-scale testing to burst also enables a critical review of the reported feature dimensions from ILI or other NDT to reality. In many ways, this large-scale testing is an evolution of the laboratory testing. The aim of this paper is to present a summary of the large-scale testing performed by Consumers Energy on pipes containing SCC that have been removed from service. The learnings from these tests are proving invaluable in terms of understanding the threat and how to manage the results from feature assessment calculations. This proactive approach of testing pipes removed from service helps Consumers to manage their pipeline and offers tremendous learning to the industry.

Paper 6

9:00
Thursday, February 20

Individual Anomaly Sizing Certainty on MFL Data

Christopher Hermes, Niklas Wilming (ROSEN Group)

Abstract

Paper 6

In corrosion management, the majority of pipeline operators utilize in-line magnetic flux leakage (MFL) inspection as the primary source of information for integrity decision-making. In-line inspection (ILI) service companies provide anomaly dimensions (length, width, depth) and general sizing accuracy tables that specify the expected uncertainties for each POF anomaly dimension class. These tables represent “population specifications” and, as such, provide tolerances that are met at a certain level of statistical confidence, typically stated at 80% or 90%. Due to various influencing factors, the true tolerance of an individual anomaly may well be lower – or occasionally higher – than the listed value.
Integrity assessments, however, apply the population specification to all the individual anomalies called by ILI. This approach can lead to suboptimal decisions: indications selected for repair or replacement in reality may not require any action, while other anomalies not considered in the action plan in reality should be addressed.

As an improved method, this paper proposes an individual anomaly sizing certainty by using posterior distributions over length, width and depth and its propagation to the pressure assessment to enhance the corrosion assessment. Using the latest artificial intelligence methodology, namely Invertible Neural Networks (INN), the paper demonstrates the feasibility and validity of the individual sizing certainty estimation by comparison to verification results.

Paper 7

10:30
Thursday, February 20

A Risk-Based Approach to Circumferential Stress Corrosion Cracking

Mark Wright (ROSEN Group)

Abstract

Paper 7

Inspection technology and assessment methods are currently insufficient to manage the increasingly common threat of circumferential stress corrosion cracking (CSCC) in pipelines. This paper will examine a range of novel techniques, that build into a risk based approach, which can be used to predict and identify locations susceptible to CSCC. This data driven approach uses a range of inline inspection and other data sets to build insights into the condition of the pipeline and the potential causes of CSCC. A selection of real world examples will be presented to demonstrate some of the possibilities and explain residual uncertainties. The data will then be combined into a risk based approach to demonstrate how the methodology supports integrity management decisions.

Paper 8

11:30
Thursday, February 20

A Fistful of Data

Roland Palmer-Jones (ROSEN Group)

Abstract

In-line inspection (ILI) data tells us about the condition of a pipeline. Integrity engineers often make expert judgements and mentally classify the condition as good or bad, based on the type, number and severity of...

Paper 8

In-line inspection (ILI) data tells us about the condition of a pipeline. Integrity engineers often make ‘expert’ judgements and mentally classify the condition as ‘good’ or ‘bad’, based on the type, number and severity of features reported. If the condition seems good, then we expect relatively straightforward and inexpensive integrity management. If the condition seems bad, then we brace ourselves for more work and high costs. Are these expert judgements of ‘good’ and ‘bad’ valid, and can they be made more rigorous?

To answer this question, we began by exploring ILI results for over 1000 pipelines, using descriptive analytics techniques. For each pipeline, we defined two simple metrics to characterize their condition – the number of corrosion features per kilometer, and the probability of exceedance. By comparing these metrics on a global scale we proposed some definitions of ‘good’ and ‘bad’. That preliminary work was published at PPIM in 2019. To further evaluate these definitions and extend the usefulness we have more recently expanded the database to over 5000 pipelines and also considered additional condition metrics such as corroded area. In this paper we present results from this extended database and investigate changes when compared with the 1000 pipeline database.

Paper 9

14:00
Thursday, February 20

Integrated Material Property Verification - Combining State-of-the-art ILI and In-Ditch Testing

Simon Slater, Christopher De Leon (ROSEN Group), Simon Bellmare, Dr. Steven Palkovic (Massachusetts Materials Technologies)

Abstract

Paper 9

Driven by safety and added regulatory requirements, operators are working diligently to characterize the material properties of pipe within their assets. Opportunities to remove pipe from the ground and perform traditional mechanical testing in a laboratory are limited. Fortunately, operators are able to use a combination of enhanced ILI and state-of-the-art in-ditch testing to characterize material properties. This paper presents the most robust process available to ensure accurate data is collected – from the segments where it is required and with statistical relevance.
ILI establishes a baseline that is used to determine where excavations are required and to align opportunistic digs with a unique knowledge of what is in the pipeline, aligned with operator records. In-ditch testing is used to gather accurate and complete information from the excavation;
it enhances the verification process and increases the confidence that the material properties are adequately characterized. The product is compliant with traceable, verifiable and complete (TVC) pipeline material properties that can be used for effective integrity programs and to satisfy regulatory requirements. Close

Paper 10

10:00
Friday, February 21

Improved Methods for Sizing Metal Loss in Dents for ECA

Rhett Dotson, Fernando Curiel, Luis Sacramento (ROSEN Group), Jacob Duska, Zach Locks (TC Energy)

Abstract

Paper 10

Dents interacting with metal loss remain as a significant challenge to operators. Existing regulations require that dents with metal loss be treated as immediate repairs or 60-day repairs, resulting in costly excavations for many operators. At the time when these regulations were written, it was not clear whether in-line inspection technologies could discriminate the nature of the metal loss (i.e. corrosion or mechanical damage) or provide accurate sizing. Furthermore, advanced analysis techniques such as finite element analysis were limited, and fitness-for-service evaluations were not common. While the technological hurdles regarding evaluating interacting dent and metal loss features have been overcome, sensor lift-off remains a challenging issue for magnetic flux leakage (MFL) inspection tools, as sizing accuracy degrades at larger lift-off distances.
Until recently, the sensor lift-off issue limited the ability to perform engineering critical assessments (ECA) because the metal loss in dent features could not be confidently sized. This study demonstrates how integrated lift-off sensors can be used to quantify the lift-off as the MFL sensors pass over a dent. This technology integration has allowed the confident application of sizing specifications for many dents with metal loss, thereby permitting robust ECAs. Several case studies are examined in this paper, demonstrating how the integrated MFL and lift-off technology can serve to reduce excavations while still ensuring safe pipeline operations.

Papers

Pipeline Pigging & Integrity Management Conference & Exhibition (PPIM) 2020

You are here:

Crack Management

Pipeline Material Verification

In-Field Validation Service

NIMA - Elevating Safety

Virtual–Dig Up

Ready for Hydrogen

Papers

Plenary opening session

Beyond Compliance ...

Abstract

Plenary opening session

Paper 1

Calculation of a laser-scan-like 3D defect profile from conventional MFL Data

Abstract

Paper 1

Paper 2

Machine Learning to Support Risk and Integrity Management

Abstract

Paper 2

Paper 3

Generation and monitoring of synthetic crack-like features in pipeline materials using cyclic pressure loading

Abstract

Paper 3

Paper 4

Pipeline GIS and Mega Rule Part 1: Material Property Verification and the System of Record

Abstract

Paper 4

Paper 5

Burst Testing of Pipes Containing Stress Corrosion Cracking

Abstract

Paper 5

Paper 6

Individual Anomaly Sizing Certainty on MFL Data

Abstract

Paper 6

Paper 7

A Risk-Based Approach to Circumferential Stress Corrosion Cracking

Abstract

Paper 7

Paper 8

A Fistful of Data

Abstract

Paper 8

Paper 9

Integrated Material Property Verification - Combining State-of-the-art ILI and In-Ditch Testing

Abstract

Paper 9

Paper 10

Improved Methods for Sizing Metal Loss in Dents for ECA

Abstract

Paper 10