Leak Detection

Versatile technology for Leak Detection, Third Party Interference and Integrity Assessment applications: Vibroacoustics

Versatile technology for Leak Detection, Third Party Interference and Integrity Assessment applications: Vibroacoustics
Versatile technology for Leak Detection, Third Party Interference and Integrity Assessment applications: Vibroacoustics
Leak detection, TPI (Third Party Interference) and asset integrity are crucial topics in pipeline monitoring, although they often require costly procedures and systems. In order to support the pipeline integrity management, Eni S.p.A, in collaboration with Solares JV, developed the e-vpms® (Eni Vibro-acoustic Pipeline Monitoring System). This...

Novel Classification Of Leak Detection And Third-Party Intrusion Enabling Best-In-Class False Alarm Rate

Novel Classification Of Leak Detection And Third-Party Intrusion Enabling Best-In-Class False Alarm Rate
Novel Classification Of Leak Detection And Third-Party Intrusion Enabling Best-In-Class False Alarm Rate
We demonstrate PrismaFlowTM’s best in class events det ection and classification capabilities accompanied by negligible False Alarm Rate (FAR). A 35 km long pre-depl oyed optical cable inside a conduit was used as the sensor. Originally deployed for communication purposes, the optical cable, running along the infrastructure, was placed along highly...

Large Stand-Off Magnetometry (LSM) for Buried Pipeline Inspection - Experimental study: Influence of dent depth on residual magnetic signal

Large Stand-Off Magnetometry (LSM) for Buried Pipeline Inspection - Experimental study: Influence of dent depth on residual magnetic signal
Large Stand-Off Magnetometry (LSM) for Buried Pipeline Inspection - Experimental study: Influence of dent depth on residual magnetic signal
Dents are among the anomalies which may be a threat to safe operation of pipelines. Dents are characterized by plastic deformation, which causes changes in the magnetic properties of the ferromagnetic pipe wall. Skipper NDT, a company at the forefront of LSM technology, conducted trials to characterize changes in magnetic properties around dents...

A new parametric study based on the Proper General ized Decomposition for the evaluation of the seismic vulnerability of buried pipelines

A new parametric study based on the Proper General ized Decomposition for the evaluation of the seismic vulnerability of buried pipelines
A new parametric study based on the Proper General ized Decomposition for the evaluation of the seismic vulnerability of buried pipelines
Pipelines related to industrial supplies such as oil or gas are a key p art of modern development, so it is important to ensure their appropriate response to a seismic action. The same applies to drainage or water supply in contemporary cities. Structural analysis of pipelines is a well-estab lished topic in engineering practice. In this paper, we...

Machine Learning Approach to Distributed Acoustic Sensors (DAS) for Securing Pipelines in Urban Areas

Machine Learning Approach to Distributed Acoustic Sensors (DAS) for Securing Pipelines in Urban Areas
Machine Learning Approach to Distributed Acoustic Sensors (DAS) for Securing Pipelines in Urban Areas
Third party interference is one of the leading causes of pipeline failures and accidents that create great risk for safety and environment, as well as revenue loss for the operators. Especially in urban areas unauthorized and uncoordinated infrastructure and construction works pose serious threat to liquid and gas pipelines. Effective detection of...

Prediction of Leak Mass Rate in High-Pressure Gas Pipeline

Prediction of Leak Mass Rate in High-Pressure Gas Pipeline
Prediction of Leak Mass Rate in High-Pressure Gas Pipeline
Gas pipeline leakage poses great threat to the environment pollution and system security. The gas leak mass rate is a key index in the assessment of risk level during pipeline leakage. In this study, compressed air flow in a high-pressure pipeline with leakage is considered, and the leak mass rate is investigated experimentally and numerically...

Pipeline Leak Detection via Machine Learning

Pipeline Leak Detection via Machine Learning
Pipeline Leak Detection via Machine Learning
As physical entities, pipelines are subject to numerous points of failure including corrosion, mechanical damage, and natural hazards. Despite being infrequent, pipeline failure can have disproportionate consequences resulting from environmental clean-up and lost production. Best practices in pipeline risk management employ both leak-prevention and...

Advanced Detection Technologies and Collaborative Information Systems for Leak Detection and Response

Advanced Detection Technologies and Collaborative Information Systems for Leak Detection and Response
Advanced Detection Technologies and Collaborative Information Systems for Leak Detection and Response
A recent newcomer in the global energy mix, natural gas will represent the second biggest share after oil by 2040 , according to the International Energy Agency (IEA). Demand on natural gas is rising globally with the economic growth of developing countries and the significant move from coal to gas initiated by governments to meet the challenge of...

Simplification Improves Batch-tracking Accuracy in Pipeline with Slack Conditions

Atmos International
Atmos International
A “lean model” that minimizes uncertainties by simulating only the necessary characteristics for batch tracking proves to be more accurate than complex models that make a plethora of assumptions in attempting to model every single characteristic of pipelines with extreme elevation changes and slack. Energy supply chains require energy companies to...