A Review of Optimization Methods for Pipeline Monitoring Systems: Applications and Challenges for CO 2 Transport

Teke Xu, Sergey Martynov () and Haroun Mahgerefteh
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Teke Xu: Department of Chemical Engineering, University College London, Gower Street, London WC1E 7JE, UK
Sergey Martynov: Department of Chemical Engineering, University College London, Gower Street, London WC1E 7JE, UK
Haroun Mahgerefteh: Department of Chemical Engineering, University College London, Gower Street, London WC1E 7JE, UK

Energies, 2025, vol. 18, issue 14, 1-19

Abstract: Carbon Capture and Storage (CCS) is a key technology for reducing anthropogenic greenhouse gas emissions, in which pipelines play a vital role in transporting CO 2 captured from industrial emitters to geological storage sites. To aid the efficient and safe operation of the CO 2 transport infrastructure, robust, accurate, and reliable solutions for monitoring pipelines transporting industrial CO 2 streams are urgently needed. This literature review study summarizes the monitoring objectives and identifies the problems and relevant mathematical algorithms developed for optimization of monitoring systems for pipeline transportation of water, oil, and natural gas, which can be relevant to the future CO 2 pipelines and pipeline networks for CCS. The impacts of the physical properties of CO 2 and complex designs and operation scenarios of CO 2 transport on the pipeline monitoring systems design are discussed. It is shown that the most relevant to liquid- and dense-phase CO 2 transport are the sensor placement optimization methods developed in the context of detecting leaks and flow anomalies for water distribution systems and pipelines transporting oil and petroleum liquids. The monitoring solutions relevant to flow assurance and monitoring impurities in CO 2 pipelines are also identified. Optimizing the CO 2 pipeline monitoring systems against several objectives, including the accuracy of measurements, the number and type of sensors, and the safety and environmental risks, is discussed.

Keywords: pipeline transport network; monitoring systems; optimization; sensor placement; algorithms (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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