Leak Detection

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...