Digitalization

From Pipelines to Home Heating: The Digital Transformation of Natural Gas Distribution

From Pipelines to Home Heating:  The Digital Transformation of Natural Gas Distribution
From Pipelines to Home Heating: The Digital Transformation of Natural Gas Distribution
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...

New Generation of AI Techniques Applied to Third Party Interference and Leakage Detection on Pipelines

New Generation of AI Techniques Applied to Third Party Interference and Leakage Detection on Pipelines
New Generation of AI Techniques Applied to Third Party Interference and Leakage Detection on Pipelines
This paper presents a pipeline monitoring system designed to detect, locate, and classify leakages and Third-Party Interference (TPI) incidents 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...

Hazard Based Protection of Gas Infrastructure Facilities against Cyber-Physical Attacks

Hazard Based Protection of Gas Infrastructure Facilities against  Cyber-Physical Attacks
Hazard Based Protection of Gas Infrastructure Facilities against Cyber-Physical Attacks
The rapid growth in digitalization and automation results in industrial 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...

Overcoming data access challenges to provide an effective leak detection system

Overcoming data access challenges to provide an effective leak detection system
Overcoming data access challenges to provide an effective leak detection system
As pipeline industry challenges continue to grow, it’s never been more important to make maximum use of the data available for leak detection. Crucial to this is the deployment of hardware that allows pipeline operators to access more data, resulting in a more effective leak detection system. In this article, Sales and Senior Research Engineer...

Software-based assessment of hydrogen-readiness of pipelines supported by GIS data

Software-based assessment of hydrogen-readiness of pipelines supported by GIS data
Software-based assessment of hydrogen-readiness of pipelines supported by GIS data
This article describes an approach to the assessment of steel pipelines regarding their potential suitability for hydrogen transportation. The assessment is made based on pipeline inventory data available in georeferenced form in a GIS, as well as in supplementary databases, and uses the software platform trascue. PIMS by GEOMAGIC GmbH, combined...

Faster Realization of Infrastructure Projects

Faster Realization of Infrastructure Projects
Faster Realization of Infrastructure Projects
Shortly after the war in Ukraine had begun, it became clear that Germany needed to diversify its sources of natural gas supply to reduce its dependency and ensure its national energy security. The import of liquefied natural gas (LNG) through the Wilhelmshaven port required a strong connection to the national gas transmission network. OGE had to...

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...

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...