Multi-site CO 2 Sequestration Optimization using a Dynamic Program- ming Approach

Increased greenhouse gas emissions, resulting from our heavy dependence upon fossil fuels, have been found to be directly related to global warming. Global warming may lead to adverse conditions, such as the melting of polar ice caps, raised ocean levels, as well as altered weather patterns producing higher intensity hurricanes and storms. While technological advances, public education, and enacting policy changes are excellent long-term solutions to this problem, carbon sequestration (CS) in addition to other short term solutions may provide a bridge to a sus- tainable future. Unfortunately, leakage of sequestrated CO 2 may contaminate air and water re- sources as well as adversely affect plant and animal life. These risks must be fully understood and minimized before implementation. A preliminary decision support system (DSS) has been constructed to optimize CS at a given number of potential injection sites, with the goal of minimizing the total cost of CO 2 leakage while meeting a specified sequestered mass target. This DSS uses a graphic user interface (GUI) and employs CSUDP, a generalized dynamic programming software, as an optimization driver. A semi-analytical leakage model was integrated into CSUDP's objective function to estimate leakage costs. Based upon work by Nordbotten et al. (2009), this model quantifies the mass of CO 2 leakage through weak areas, such as abandoned oil wells, of the caprock overlying the injected aquifer. The resulting DSS uses a wide range of geological, economical, and infrastructural parameters to output optimal CO 2 injection rates and injection durations for each site.