Static and dynamic estimates of CO2 storage capacity in two saline formations in the UK

Estimation of CO2 storage capacity is a key step in the appraisal of CO2 storage sites. Different calculation methods may lead to widely diverging values. The compressibility method is a commonly used static method for estimating storage capacity of saline aquifers: it is simple, easy to use and requires a minimum of input data. Alternatively, a numerical reservoir simulation provides a dynamic method which includes Darcy flow calculations. More input data are required for dynamic simulation, and it is more computationally intensive, but it takes into account migration pathways and dissolution effects, so is generally more accurate and more useful. For example, the CO2 migration plume may be used to identify appropriate monitoring techniques.

Two typical saline aquifer storage sites were analysed using both static and dynamic methods. One site has a comparatively simple geology, while the other has a more complex geology. For each site both static and dynamic capacity calculations were performed. CO2 injection for 15 years was followed by a closure period lasting thousands of years. The proportion of dissolved CO2 and the proportion immobilised by pore scale trapping were calculated.

The results of both geological systems show that the migration of CO2 is strongly influenced by the local topography of the upper surface of the aquifer formation. The calculated storage efficiency for the first site varied between 0.5% and 1% of total pore volume, depending on whether the systems boundaries were considered open or closed. Simulation of the deeper, more complex geological system gave storage capacities as high as 2.75%.

This work is part of the CASSEM (CO2 Aquifer Storage Site Evaluation and Monitoring) integrated study to derive methodologies for assessment of CO2 storage in saline formations. Although, static estimates are useful for initial assessment, we demonstrate the value of performing dynamic storage calculations, and the opportunities to identify mechanisms for optimising the storage capacity.