Carbon capture and storage (CCS) is a key technology that directly removes industry driven CO₂ to achieve carbon neutrality. In the process of CCS, it is necessary to monitor whether injected CO₂ is properly stored and not leaking. The behavior of CO₂ can be investigated using a 4D seismic survey that compares seismic data before and after injection. We proposed a two-step monitoring with diffraction-angle filtering (DAF) to effectively locate the CO₂ plume. Because DAF allows us to control wavenumber components, the gradient of full-waveform inversion (FWI), which is the first step, is composed of low-wavenumber components, and reverse time migration (RTM) for seismic imaging is carried out with high-wavelength components. To verify our method, we implemented FWI and RTM with and without DAF using the velocity model in the Volve oil field in the North Sea. Numerical examples show that the CO₂ plume is properly detected from the difference between baseline and post-injected survey and the extension of the reflective boundary is improved compared to the results of the conventional method. With our proposed method, local minima problem is mitigated in FWI, and the boundaries between layers can be clearly distinguished in RTM.

Spearheaded by the European Union and the Intergovernmental Panel on Climate Change (IPCC), carbon capture and storage (CCS) has recently been emphasized as an essential strategy for addressing climate change. South Korea is pursuing CCS projects such as the Donghae-1 Gas Field and the Gunsan Basin Project, and site characterization studies are being progressively conducted. This paper presents the Smeaheia Project, a large-scale CCS initiative in Norway, as a reference case for developing large-scale CCS projects in Korea. First, we examine the status of large-scale offshore CCS projects based on the geological characteristics of Norway. Next, we assess the suitability of the Smeaheia storage site based on geological and geophysical characterizations and investigate the current development status of the ongoing Smeaheia CCS project. Finally, we confirm important insights from the Smeaheia

Given the potential influence of seismic anisotropy on multi-channel seismic data acquired over sedimentary basins, applying an optimal anisotropic time-lapse seismic imaging technique to accurately estimate the injected CO₂ plume is imperative. This study conducts acoustic multi-parameter assumption full-waveform inversion (FWI) based on the elliptical anisotropy to enhance the accuracy of time-lapse seismic monitoring results at the Sleipner field. The Sleipner project is the pioneering commercial-scale offshore carbon capture and storage (CCS), marking the successful implementation of time-lapse seismic surveys to monitor the injected CO₂ plume. To validate the necessity of anisotropic time-lapse FWI at the Sleipner field, we construct an initial anisotropic velocity model using Backus averaging. Subsequently, we compare the accuracy of the velocity structure obtained with isotropic and anisotropic FWI starting from the same initial model. Consequently, we confirm that the elliptical anisotropic time-lapse FWI significantly enhances accuracy, as demonstrated by the improved matching of synthetic data derived from anisotropic FWI to the real data, compared to the isotropic FWI results.

The Northern Lights carbon capture and storage (CCS) project in Norway was examined, focusing on the geological suitability of the Aurora site for large-scale CO 2 storage. This project leverages the geological stability of the Johansen and Cook formations; the high porosity and permeability of the sandstone layers; and the Drake formation, a shale layer that serves as a cap rock. Fault zones such as Svartalv and Tusse act as lateral barriers to CO 2 migration, whereas a triangular trap structure enhances storage security. These geological features ensure sufficient storage capacity and effective containment, positioning the Northern Lights projects as a promising model for commercial CCS hubs across Europe. This project highlights the potential for scalable CCS development and offers valuable insights for other projects in the site characterization phase through the collaboration with industrial partners.