An Overview on Pipeline Leakage in Carbon Capture Storage

Pipeline leakage in Carbon Capture and Storage (CCS) systems poses a critical threat to the effectiveness and reliability of carbon sequestration technologies. As pipelines serve as the primary mode of CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> transport, their integrity is vital to prevent leaks that can result in environmental damage, safety hazards, and economic losses. This paper overviews conventional techniques such as pressure monitoring and visual inspections, as well as advanced technologies like fibre optic sensors, acoustic emissions, and machine learning models. It compares detection methods by accuracy, scalability, and realtime potential in CCS applications. Simulation-based modelling and deep learning are explored for image-based leakage localisation. Limitations and applicability to CCS are evaluated. Additionally, the study explores the environmental and economic implications of CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> leaks and discusses relevant industry standards. A future roadmap is proposed to enhance monitoring, predictive maintenance, and material design.