Recognition of leak CO2 with wavelet analysis based on correlation monitoring between CO2 and O2 in atmosphere

Abstract It is necessary to monitor and identify CO 2 leakage from geosequestration project. Some experiments were designed to test the feasibility of characterization and recognition method for CO 2 leakage based on correlation analysis between atmospheric CO 2 and O 2 . The monitoring results showed that atmospheric CO 2 had a good linear relationship with O 2 , especially in the day time. The variations of CO 2 and O 2 were influenced by the weather condition. The results of emission experiments proved the capability of coupling monitoring atmospheric CO 2 and O 2 to recognize the abnormal CO 2 signal due to leakage. Moreover, two parameters, ALF (apparent leakage flux) and ALFs (apparent leakage flux based on surplus variable) were used to distinguish CO 2 leakage in real time. The monitoring results verified that it was feasible to identify CO 2 leakage with these two parameters. Compared with the results after median filter, the abrupt leakage signal can be more easily recognized with that after wavelet filter. ALFs can be applied to estimate the elevated concentration due to leakage, which can also be predicted by interpolating with related variation of atmospheric O 2 . ALF reflects the relative leakage rate. Therefore, it is practicable to identify leakage event in real time with the method proposed in this paper.