Barham S. Mahmood
Koya University, Iraq
Title: Optimization of CO2 storage in deep saline aquifer using the Raven software
Biography
Biography: Barham S. Mahmood
Abstract
Determining storage capacity in a deep saline aquifer is constrained by the capability of the formation to disperse additional pressure which is generated by CO2 injection (pressure build-up)and migration of CO2 at the edge of the aquifers (CO2 leakage) . Therefore, in order to accurately predict the storage capacity it is important to consider these two factors before a CO2 project proceed. In term of optimization scenario for CO2 storage in deep saline aquifers, it is usually focused on the key optimization parameters such as well location, number of well, well completion and injection rate to obtain a desire injectivity, maximize CO2 storage as much as possible and provide risk assessment with reasonable confidence In this project two cases were considered. An optimization study has been carried out in one sector of Bunter model (Dome A) and among the relevant parameters mentioned above three parameters has been optimized; injection rate, well location and well completion by applying multi-objective particle swarm optimization algorithm using Raven software. The result of this study shows that in case two when changing the number of wells from 5 to 7 injectors the possible storage capacity for dome A is increased from 139 Mt to 145 Mt. However, the maximum CO2 leakage did not reach the criterion of 0.1%/year. Thus, to determine the maximum safe volume of CO2 further extended CO2 injection is required. In terms of pressure build-up, the result shows that the well bottom-hole pressure in observation well for both cases never exceed the fracture pressure of the Bunter formation. The result also indicates that the MOPSO algorithm is promising in obtaining the desired objective to improve storage capacity significantly while reducing the pressure build-up and CO2 migration.