Assessment and uncertainty quantification of onshore geological CO2 storage capacity in China

We provide a probabilistic assessment of CO2 storage capacity in major sedimentary basins in China. Our approach embeds constraints associated with the increase of reservoir pore pressure due to injection of CO2 in the presence of resident brine. Pressure build-up must be limited to avoid fault reactivation, caprock failure, and possible leakage, resulting in more conservative estimates of CO2 storage capacity as compared to volumetric estimates.We rely on a numerical Monte Carlo framework considering uncertainty in the values of reservoir size and major geological formation attributes (i.e., absolute permeability, porosity, and reservoir compressibility). Our work shows that 10 major basins can potentially store, on average, 1350 Gt of CO2 during the next 30 years (lower and upper quartiles being 1100 and 1700 Gt of CO2, respectively). This far exceeds the likely amount (up to 175 Gt of CO2) required to be stored by 2050. Our analysis also suggests that 6 basins (located close to the largest emission areas) can store about 93 Gt (on average) of CO2 during the next 30 years. Underground carbon storage in China, coupled with other possible solutions, could meet the aims of the Announced Pledges Scenario (International Energy Agency) to mitigate global warming by 2060.We also perform a global sensitivity analysis to determine how our predictions of storage capacity may be affected by uncertainties in the simulation model input parameters. Moment-based global sensitivity metrics suggest that geological formation attributes are major sources of uncertainty, significantly affecting model outputs and the associated uncertainty.

Automated summary

We conducted a probabilistic assessment of CO2 storage capacity in major sedimentary basins in China, showing that 10 major basins have the potential to store an average of 1350 Gt of CO2 in the next 30 years. Our analysis suggests that underground carbon storage in China, combined with other solutions, could help meet the goals of mitigating global warming by 2060, as per the Announced Pledges Scenario (International Energy Agency). Geological formation attributes were found to be major sources of uncertainty affecting model outputs and associated uncertainty.