Systematic methods for smart management of CO₂ transport and injection systems

Short summary of the project

Future CCS/CCUS systems will require the use and/or establishment of massive pipe transportation networks and shipping routes that comingle the production from CO₂ sources and transport it to injection wells over long distances. This PhD project addresses challenges related with the optimal operational management of such systems. The research will be carried out using numerical models programmed by the candidates or, alternatively, commercial software. 

There will be several challenges when operating (and designing) such systems, such as:

• Ensuring high system availability to avoid interruptions in the upstream processes
• Handling variations in source and injection conditions
• Handling start-up, shutdown
• Ensuring energy-efficient operations
• Ensure structural integrity to the system considering the temperature changes along it and its variations in time as conditions change

The objectives are the following:

• Development of a decision support system for the optimal management of CO₂ gathering, transportation and injection CO₂ networks, considering multiple sources and injection points, and shipping routes.
• Consider the effect of uncertainties, and short (e.g. hours, and days) and long term variations (weeks, months) at the source and injection.
• Perform multi-objective non-linear optimization to include compression energy efficiency and consumption
• Active exploitation of storage in the pipe network (line-pack) to accommodate for variations in the source and injection volumes.

Gaps addressed: According to input from Gassco, the points addressed in this project are very relevant for the Norwegian natural gas pipe network, which is the reason why they are supporting a PhD project in BRU21. In this project we will study similar issues but applied to CO₂ pipe networks and considering shipping routs.

This project will consider previous work. Study cases will be developed with the interested partners.

The use of AI techniques such as machine learning, to provide decision support or create data-driven proxy models will be studied during this project.

Innovation potential

• An enabler for the efficient management and design of CO₂ pipe networks that enables disposal of CO₂ produces on and offshore
• Solving a relevant challenge for the energy transition
• Reduction of energy usage and improving the economy of the CO₂ value chain
• Further development into a software/including the methods in existing software.