UKCCSRC Call 2 Project: CO2 Flow Metering through Multi-Modal Sensing and Statistical Data Fusion

Measurement and monitoring of CO2 flows across the entire CCS chain are essential to ensure accurate accounting of captured CO2 and help prevent leaking during transportation to and from storage sites. This particular R&D need has been identified as one of the highest priority areas in the latest APGTF Strategy Report and in the UKCCSRC RAPID Handbook as well as in a recent study by NEL. The need for addressing measurement uncertainty and its importance for CO2 flows is a key factor in the CCS chain. The accurate measurement of CO2 is also vital to lift the strict regulations from legislative bodies off the full deployment of CCS and create a more positive public perception towards CCS. In addition, it is imperative to investigate the flow metering aspects of CO2 to inform the legislators and regulators and to have this underpinning knowledge available to the providers of the design, build and operation of CCS plants. In this project a cutting-edge technology for the measurement of CO2 flows in CCS pipelines will be developed. The technology will incorporate multi-modal sensing and statistical data fusion techniques. General-purpose flow sensors, including Averaging Differential Pressure, ultrasonic and Coriolis together with temperature, pressure and electrical impedance transducers, will be utilised to create a prototype multi-modal sensing system. A statistical data fusion method based on Bayes' rule for combining prior and observation information will be developed to integrate the outputs of the sensors and transducers. Various statistical data fusion models will be developed off-line and optimal data fusion models will be selected for on-line implementation. Meanwhile, a dedicated CO2 mass flow reference platform will be built using precision weighing techniques and its uncertainty will be established. Extensive experimental work will be conducted on the CO2 mass reference platform after implementing the on-line statistical data fusion models. The multi-modal sensing system will then be extensively tested under controlled flow conditions which resemble practical CCS conditions. The measurement uncertainty for each selected data fusion model will be reported together with the implication of costs, which will be a very informative source for users, manufacturers and researchers. Finally, the multimodal sensing system will be scaled up with the support of the industrial partner and evaluated on their large line (>DN250) flow test facility under simulated flow conditions. Effects of impurities in the CO2 flow on the performance of the flow measurement system will also be studied. Findings from the project will be disseminated to the UKCCSRC and a wider community. Grant number: UKCCSRC-C2-218.