Numerical study of underground CO2 storage and the utilization in depleted gas reservoirs
The emission of atmospheric CO2 is the main contributor to global warming and climate change. Carbon capture and storage (CCS) is considered as the most promising technology for slowing down the atmospheric CO2 emissions. Meanwhile, CCS is beneficial for the circulation carbon economy. However, CCS has not been implemented on large scale because of the related risks and the lack of economic incentives. This thesis attempts to focus on these two problems and provide some strategies to address them. Regarding the risks associated with CCS, a parametric uncertainty analysis for CO2 storage was conducted and the general role of different geomechanical and hydrogeological parameters in response to CO2 injection was determined. Regarding the financial incentives of CCS operation, this thesis attempts to increase the cost-effectiveness of CCS through co-injecting CO2 with impurities associated with enhanced gas recovery (CSEGR) and using CO2 as cushion gas in the underground gas storage reservoir (UGSR). In order to understand the thermal-hydrological-mechanical (THM) process of CO2 storage, the THM coupled simulator TOUGH2MP (TMVOC)-FLAC3D was developed. By using the developed TOUGH2MP (TMVOC)-FLAC3D simulator, numerical simulation for hundreds of sampled data was performed for results generated by the Quasi-Monte Carlo method. Based on the simulation results, the general role of different geomechanical and hydrogeological parameters was determined in response to CO2 injection using distance correlation. In addition, a risk factor was defined to characterize the risks of the caprock due to CO2 injection. The results showed that the reservoir permeability and the injection rate are the two most important factors in determining the pressure change. Moreover, the reservoir Young’s modulus plays the most vital role in formation deformation including vertical displacement. The pressure change exhibits a much closer correlation with the risk factor in comparison to the formation deformation, indicating the importance of pressure change in the integrity assessment of the caprock. By using the machine learning approach in support vector regression (SVR), the SVR surrogate model was well-trained based on the data regarding simulated results, and its reliability was verified using the test data. Thereafter, the formation response including the pressure change as well as formation deformation, can be predicted using the trained SVR surrogate model within a very short time. The methods and working scheme applied in this work can be used to guide time and effort spent mitigating the uncertainty in these parameters to acquire trustworthy model forecasts and risk assessments in CCS projects. Attempting to decrease the cost of CCS operation, CO2 injection with impurity gas, i.e., N2 and O2, into a depleted gas reservoir was investigated. The impacts of the key parameters on the performance of CO2 storage and CSEGR were analyzed in detail. The results showed that the effect of impurities on CO2 storage capacity is dependent on the reservoir pressure and temperature conditions, and the concentration of impurities. The depleted gas reservoir with a relatively low temperature and low irreducible water saturation is favorable to the CO2 storage capacity. A low primary gas recovery for the depleted gas reservoir is in favor of CSEGR, while it is suitable for dedicated CO2 storage when the primary gas recovery is high. In addition, it is suggested to produce the CH4 as possible before the operation of CO2 storage and CSEGR. The chromatographic partitioning phenomenon may occur when N2 and O2 were co-injected with CO2 into depleted gas reservoirs, which could be used as a monitoring strategy for the CO2 front and potential CO2 leakage. In addition to the solubility and concentration of the impurity gas would affect this phenomenon, there is a critical water saturation for the occurrence of significant chromatographic partitioning phenomenon associated with determined type and concentration of impurity gas. To increase the cost-effectiveness of CCS, the suitability of utilizing CO2 as the cushion gas in the UGSR was analyzed based on the geological parameters of Donghae depleted gas reservoir in Korea. The cyclic CH4 production and injection were conducted over a period of 15 years to acquire the mixing behavior of CO2 and CH4 in a relatively long-term period. The results showed that the maximum CO2 concentration that can be used for cushion gas is 9% under the condition of production and injection for 120 and 180 days in a production cycle at a rate of 4.05 and 2.7 kg/s, respectively. The typical curve of the mixing zone thickness can be divided into four stages, i.e., the increasing stage, smooth stage, suddenly increasing stage, and periodic change stage. The CO2 fraction in the UGSR, reservoir permeability, and production rate have a significant effect on the breakthrough of CO2 in the production well, while the effect of water saturation and temperature is neglectable. For the purpose of utilizing more CO2 as cushion gas in the UGSR, CO2 is supposed to be injected for supplementation during the operation of UGSR. Generally, the parametric uncertainty analysis conducted in this thesis is beneficial for the risk assessments in CCS projects. Co-injecting CO2 with impurities associated with CSEGR and utilizing CO2 as cushion gas in UGSR are favorable for improving the economic incentives of CCS operation. Therefore, this thesis is beneficial for promoting the application of CCS and mitigating the atmospheric CO2 emissions.
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