Optimization of CO2 Storage in Saline Aquifers using the Raven Software
Barham S Mahmood*
Institute of Petroleum Engineering, Heriot Watt University, Edinburgh Campus, Edinburgh EH14 4AS, UK
- *Corresponding Author:
- Barham S Mahmood
Institute of Petroleum Engineering
Heriot Watt University, Edinburgh Campus
Edinburgh EH14 4AS, UK
Tel: + 9647703605782
E-mail: [email protected] koyauniversity.org
Received Date: August 03, 2015; Accepted Date: November 25, 2015; Published Date: December 01, 2015
Citation: Mahmood BS (2015) Optimization of CO2 Storage in Saline Aquifers using the Raven Software. J Ecosys Ecograph 5:172. doi:10.4172/2157-7625.1000172
Copyright: © 2015 Mahmood BS. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
CO2 storage in deep saline aquifer is still at its infancy and not yet matured for large scale industrial development due to the considerable uncertainties that still exist regarding storage capacity and safety. At the same time, because this is an expensive process, so engineers wish to store as much CO2 as possible within a particular saline formation. However, injecting huge amounts of CO2 into the particular saline formation pose significant technical issue such as pressure build-up and CO2 leakage. Therefore, in order to fully exploit it is potential, optimum injection strategies need to be investigated. In this paper we examine a realistic model of deep saline aquifer and conduct optimization study on some simulation parameters by applying multi-objective particle swarm optimization algorithm (MOPSO) to Enhance CO2 storage capacity and safety by, 1) Maximize total injected CO2, 2) Minimize pressure build-up in the center of the field and 3) Minimize CO2 leakage at the edges of the aquifer. The result of this study shows that when changing the number of wells from 5 to 7 injectors the possible storage capacity for dome A is increased by 4%. However, the maximum CO2 leakage did not reach the criterion of 0.1%/ year.
The results also indicate 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. Keywords: Saline aquifer; Storage risk; Pressure build-up; MOPSO Introduction As the level of CO2 rise every year, it is necessary to find a solution to this problem. Carbone capture and storage (CCS) is considered to be an important means of reducing the levels of CO2 in the atmosphere . CO2 might be stored in an oil and gas reservoir, unmineable coal