Speaker
Description
Carbon Capture and Storage (CCS) is a critical technology for reducing global CO$_2$ emissions, and ensuring safe storage requires robust monitoring methods. While seismic techniques are widely used for subsurface investigations and excel at imaging reservoir lithology, they have limitations in directly quantifying density variations. Muography, a technique utilizing cosmic-ray muons, offers high penetration power and direct sensitivity to density changes, making it a promising complementary tool for continuous CCS monitoring.
Conducting muography simulations for CCS presents a significant computational challenge, as typical storage sites lie at depths of 800-3,000 meters, with CO$_2$ plumes extending hundreds of meters requiring Monte Carlo simulation of muon transport through massive rock volumes with prohibitively long computation times. To address this, we developed a two-stage workflow using MUSIC (MUon SImulation Code) and PHITS (Particle and Heavy Ion Transport code System). MUSIC transports muons through the hundreds-of-meters-thick overburden, and PHITS then propagates surviving muons through site-specific reservoir models and muography detectors.
We also developed an open-source Fortran/Python toolkit that generates surface muons using either the CosmoALEPH or power-law spectral parametrization, applies configurable multi-detector ray-tracing filters to pre-select geometrically relevant muons, and exports directly to PHITS and Geant4 source formats. An interactive Streamlit GUI orchestrates the complete CosmoALEPH → MUSIC → PHITS pipeline with 3D visualization and solid-angle estimation, making the simulation chain accessible to the muography community.
We evaluated this proof-of-concept approach through simulations of the kilometer-scale Sleipner CCS facility under idealized conditions, and the 50-meter-scale Svelvik CO$_2$ Field Lab with more realistic detailed modeling. Our simulations demonstrate muography's capability to detect CO$_2$ plumes and resolve density changes associated with varying CO$_2$ saturation levels, providing information not directly accessible through seismic techniques alone. By offering insights into the density distribution of CO$_2$ plumes, muography can complement seismic tomography, thereby enhancing the safety, reliability, and transparency of CCS operations.