Abstract
Carbon capture, utilization, and storage (CCUS) plays a vital role in reducing CO₂ emissions. Effective CO₂ storage requires reliable monitoring to track plume movement and detect leaks. Cross-well seismic imaging is a promising approach, offering high-resolution insights by capturing transmitted energy and minimizing surface noise. Its stable acquisition setup also improves repeatability for time-lapse monitoring.
We present a novel cross-well imaging method using reverse time migration (RTM) combined with an energy norm imaging condition (ENIC) and pseudo-Hessian scaling. This approach enhances image quality by reducing incoherent energy, suppressing artifacts, and compensating for uneven illumination, thereby improving plume tracking accuracy.
Our method was tested at the Svelvik CO₂ Field Lab near Oslo, Norway. Cross-well seismic data were acquired between two wells (M3 and M4) spaced 19.8 m apart, intersecting the CO₂ injection well. The 2023 dataset included 71 P-wave sparker shots and 24 hydrophones, collected before, during, and after CO₂ injection over 25 days. Processing isolated direct arrivals and applied filtering to highlight plume-induced changes.
Imaging results revealed four distinct anomalies between 36 m and 65 m depth, consistent with CO₂ accumulation below a known sealing mud layer. The shallowest anomaly confirmed the barrier effect of the layer, while deeper plumes aligned with the injection zone. Synthetic modeling confirmed the observed scattering patterns. Comparisons showed that ENIC and pseudo-Hessian correction significantly improved resolution over conventional RTM.
In summary, our advanced cross-well RTM approach enhances CO₂ plume monitoring by improving resolution and reducing imaging artifacts, validated through field application at Svelvik.
We present a novel cross-well imaging method using reverse time migration (RTM) combined with an energy norm imaging condition (ENIC) and pseudo-Hessian scaling. This approach enhances image quality by reducing incoherent energy, suppressing artifacts, and compensating for uneven illumination, thereby improving plume tracking accuracy.
Our method was tested at the Svelvik CO₂ Field Lab near Oslo, Norway. Cross-well seismic data were acquired between two wells (M3 and M4) spaced 19.8 m apart, intersecting the CO₂ injection well. The 2023 dataset included 71 P-wave sparker shots and 24 hydrophones, collected before, during, and after CO₂ injection over 25 days. Processing isolated direct arrivals and applied filtering to highlight plume-induced changes.
Imaging results revealed four distinct anomalies between 36 m and 65 m depth, consistent with CO₂ accumulation below a known sealing mud layer. The shallowest anomaly confirmed the barrier effect of the layer, while deeper plumes aligned with the injection zone. Synthetic modeling confirmed the observed scattering patterns. Comparisons showed that ENIC and pseudo-Hessian correction significantly improved resolution over conventional RTM.
In summary, our advanced cross-well RTM approach enhances CO₂ plume monitoring by improving resolution and reducing imaging artifacts, validated through field application at Svelvik.