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Editorial: Selecting the proper inspection programs

Editorial: Selecting the proper inspection programs
Editorial: Selecting the proper inspection programs
Considering systemic approaches and effective models, with detailed steps and an integrated management program for all components and assets in any pipeline network can enhance the reliability of the network, and promote the system to the next level of excellence. Pipelines comprise of the most efficient methods of energy transportation and...

Pipeline Technology Journal 1/2024

This fist issue of the Pipeline Technology Journal - ptj in 2024 features a collection of papers on the topic of Safety & Inspection and their influence in the pipeline industry.

For the first time the journal features a new column - ptj Insights.

ptj 1-2024

The Future of Risk based Integrity Management using AI Approaches

The Future of Risk based Integrity Management using AI Approaches
The Future of Risk based Integrity Management using AI Approaches
Pipeline Integrity Management Systems (PIMS) have significantly improved the safety of pipelines in Europe and the United States. New technologies such as artificial intelligence (AI) and modern Geographic Information System (GIS) visualization can and will elevate pipeline integrity to a new level. However, challenges for pipeline integrity have...

Distributed Fiber Optic Sensing for Leak Detection: Tuning, field-testing and the future

Distributed Fiber Optic Sensing for Leak Detection: Tuning, field-testing and the future
Distributed Fiber Optic Sensing for Leak Detection: Tuning, field-testing and the future
Distributed Fiber Optic Sensing is a highly sensitive technology for leak detection that can provide rapid detection and precise locating of small leaks. The evidence from field trials and real-world leaks is becoming increasingly available and more and more pipelines are implementing the technology for leak detection. Under controlled testing, it...

Monitoring and Anomaly Detection Approaches with AI and Data Analytics for Pipelines

Monitoring and Anomaly Detection Approaches with AI and Data Analytics for Pipelines
Monitoring and Anomaly Detection Approaches with AI and Data Analytics for Pipelines
Effective monitoring and anomaly detection are fundamental prerequisites for safeguarding the efficiency, integrity and reliability of pipeline systems. Here, we explore both physics-based and machine-learning approaches for operational asset monitoring and anomaly detection, as well as evaluate their performance and appropriateness across a...

Mastering the Match: A Comprehensive Validation of Run Comparison Software Using Synthetic Data

Mastering the Match: A Comprehensive Validation of Run Comparison Software Using Synthetic Data
Mastering the Match: A Comprehensive Validation of Run Comparison Software Using Synthetic Data
This study rigorously validates run comparison (RC) software, essential for accurate corrosion growth rate assessments in pipelines, using an extensive synthetic dataset and an experimental K-nearest neighbours-based algorithm across 2,000 diverse spools. Detailed within the paper are the synthetic data generation, in-line inspection (ILI) run...

Enhancing External Corrosion Direct Assessment With Machine Learning

Enhancing External Corrosion Direct Assessment With Machine Learning
Enhancing External Corrosion Direct Assessment With Machine Learning
Operators need to keep their pipelines fit for purpose, maximize life and control costs. External corrosion is one of the main threats faced by operators, costing millions annually in identification, mitigation and repair. Although many methods exist to model the growth of corrosion features, the situation is often most complicated for “unpiggable”...

Pipeline Joint Identification using Neural Networks

Pipeline Joint Identification using Neural Networks
Pipeline Joint Identification using Neural Networks
Conventional inline inspection (ILI) tools use odometer wheels to determine the location of identified defects. On top of that, above ground markers (AGMs) are used to confirm and potentially correct for odometer wheel slippage. Free-floating unconventional ILI tools use information from a variety of sensors to accurately locate defects. Accurately...

Toward AI Data-Driven Pipeline Monitoring Systems

Toward AI Data-Driven Pipeline Monitoring Systems
Toward AI Data-Driven Pipeline Monitoring Systems
This work focuses on the application of artificial intelligence methods to enhance pipeline monitoring systems, specifically Third-Party Interference (TPI) and leak detection. A critical aspect of pipeline monitoring revolves around determining the operational state of the pipeline. This is paramount because the processing algorithms are...

Editorial: Data Science & Artificial Intelligence

Editorial: Data Science & Artificial Intelligence
Editorial: Data Science & Artificial Intelligence
W. Edwards Deming, a prominent statistician and consultant in the field of quality management during the latter half of the twentieth century, asserted that every corporation should have a skilled statistician reporting to the senior leadership so that critical decisions could be based on sound statistical evidence. The rise of data science as a...

Pipeline Technology Journal 4/2023

This last issue of the Pipeline Technology Journal - ptj in 2023 features a collection of papers on the topic of Data Science & Artificial Intelligence and their influence in the pipeline industry:

ptj 4-2023

The Arrival Oil and Gas Pipeline Monitoring with Satellite-Based Hyperspectral Imaging

The Arrival Oil and Gas Pipeline Monitoring with Satellite-Based Hyperspectral Imaging
The Arrival Oil and Gas Pipeline Monitoring with Satellite-Based Hyperspectral Imaging
Hyperspectral imagery (HSI) began in the 1980s and has been used by the U.S. government for years, but it just recently became available for commercial use. This technology has a vast range of potential applications, with oil and gas pipeline monitoring being one of the most prominent examples. HSI enables unparalleled daily global pipeline leak...

Stress Concentration Tomography with Machine Learning for Defect Severity Classification

Stress Concentration Tomography with Machine Learning for Defect Severity Classification
Stress Concentration Tomography with Machine Learning for Defect Severity Classification
Defect severity classification holds significant importance within industries that prioritize quality control. This study proposes a novel approach that applies machine learning with Stress Concentration Tomography (SCT) to effectively categorize defects’ severity. Through the utilization of machine learning algorithms, the objective is to enhance...

Pipeline 3D-Positioning at river crossing: Long-Range Magnetic Mapping via Unmanned Aerial System (UAS)

Pipeline 3D-Positioning at river crossing: Long-Range Magnetic Mapping via Unmanned Aerial System (UAS)
Pipeline 3D-Positioning at river crossing: Long-Range Magnetic Mapping via Unmanned Aerial System (UAS)
Pipeline networks traverse modern societies' national territories and can be located in areas difficult to access, such as river crossings, making maintenance logistically challenging and potentially dangerous for field personnel. In order to resolve this problem, Skipper NDT has developed an unmanned aerial system (UAS) for magnetic mapping which...

Development of a Semi-quantitative Risk Assessment Approach for Pipelines

Development of a Semi-quantitative Risk Assessment Approach for Pipelines
Development of a Semi-quantitative Risk Assessment Approach for Pipelines
Pipelines are typically designed using different practices and codes than in-plant piping. While Risk-based Inspection (RBI) quantitative methodologies have evolved and been applied for in-plant piping, e.g. API RP 581, limited methodology framework has been specified and widely used for pipelines, in a similar approach. Alternatively, for...

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