UACE: Improving acoustic monitoring and gas flux quantification techniques for marine carbon capture and storage complexes

• Day: June 16, Monday
    Location / Time: A. TERPSIHORI at 19:00-19:20
• Last minutes changes: -
• Session: 03. Advances in acoustic measurement systems: Technologies and applications
  Organiser(s): Alessandra Tesei, Matthew Schinault, Purnima Ratilal
  Chairperson(s): Matthew Schinault
• Lecture: Improving acoustic monitoring and gas flux quantification techniques for marine carbon capture and storage complexes
  Paper ID: 2328
  Author(s): Jonathan Farr, Jonathan Bull, Freya Malcher, Paul White, Stephen Robinson, Jon Helmore, Zuhaib Khan
  Presenter: Jonathan Farr
  Abstract: With over 350 Mtpa capacity of carbon capture and storage facilities in development globally as of 2023, implementation of effective monitoring strategies is necessary for public assurance, regulatory oversight and emissions trading schemes. A series of gas release experiments were devised to aid in the development of water column monitoring techniques which could be deployed above carbon capture and storage complexes, and also used to detect and quantify leakages from seabed infrastructure more generally.\n\n \n\nTwo controlled gas release experiments were completed, utilising mass flow controllers for accurate flow rates for both investigating carbon dioxide and methane, with measurements taken using active and passive acoustics and optical methods at different gas flux. Experiment 1 collected data to analyse the limitations of active sonar sensitivity to different gas flux, improve methods of gas flux calculations and the impact of gas species on detection and quantification methods. Experiment 2 collected data to investigate the effect of depth of passive quantification methods changing the depth of gas diffusion in the water column at 2m increments.\n\nTwo active monitoring data sets were also collected to investigate the use of anomaly detection algorithms for the detection of gas flux by setting up the sonar in a static position overnight and in between experiments.\n\n \n\nThrough this experimentation, we have shown the ability to use active and passive monitoring for the detection of gas flux. We have also shown there are limitations to the range of both active and passive techniques and complexity in the application of active monitoring data to train machine learning models.
• Corresponding author: Mr Jonathan Farr
  Affiliation: University of Southampton & National Physical Laboratory
  Country: United Kingdom