## 5 Discussion
It is reasonable to assume that producer P6 is strategically placed along the anticipated path of the plume for pressure maintenance, given the substantial injection rate from day 1. Producer P4 is strategically located to ensure a uniformly distributed plume. Considering the gravitational pressure differential that causes CO\({}_{2}\) to migrate towards the crest, the advancement of the resulting plume's front would be uneven. However, P4 counteracts this by moderating the pressure in its vicinity, resulting in even plume migration by the end of the CCS period, as illustrated in Figure 12.  
Finally, the remaining six producers are positioned behind the crest, in accordance with the second intuition, that is, the deceleration of the CO\({}_{2}\) plume once it reaches the crest, primarily due to density differences between CO\({}_{2}\) and the brine. At this juncture, breakthrough to the producers becomes inevitable, marking the conclusion of the injection period. It is noteworthy that the simulation ran successfully for approximately 40 years, during which the injection rate naturally decelerated due to pressure buildup. However, as depicted in Figure 13, the plume had not yet reached the producers by this point. Figure 11: Optimal well placement achieved by the proposed algorithm. Figure 12: Even plume front when CO\({}_{2}\) reaches the crest. Field pressure, depicted in Figure 14, is shown to emphasize that even after 40 years of continuous development, the aquifer has not yet reached the safety limit pressure. Pressure gradient varies due to the constraints imposed on production/injection and breakthrough rates. Overall, BO optimization successfully captured, without any explicit guidance and in a very limited number of simulation runs, the need for producers and injectors to be spaced as further apart as possible, while positioning the producers below the crest to slow down CO2 plume breakthrough. These are the two primary insights crucial for injection optimization, which an experienced engineer would typically independently deduce. Configurations deviating from these principles are deemed sub-optimal, leading to earlier CO2 breakthrough in producers. Consequently, producers are prematurely closed off, pressure builds up faster, and injection rates decline sooner, resulting in reduced total  
Figure 14: Field pressure vs. time. Figure 13: CO2 plume migration at the end of the optimal scenario’s simulation. CO\({}_{2}\) injection and less effective plume sweep efficiency. This trend is illustrated in Figure 15, where the optimal case's injection rate (blue line) is compared to a sub-optimal one (red line). Despite the optimal case having a notably higher target injection rate, it maintains this rate for over a decade longer and exhibits a more gradual decline compared with the sub-optimal scenario. In the latter, injectors are not efficiently spaced with respect to the producers; therefore, the pressure reaches the safety limit of 9000 psi in less than a decade of development. The number of producers and injectors, as well as the aquifer system, are identical in both cases. Given the engineering-oriented approach of the optimizer's solution, there is a high degree of confidence that the proposed solution is indeed optimal. However, it is essential to acknowledge the complexity introduced by the multi-dimensional nature of the input space. While the solution obtained represents a significant achievement, it is plausible that there exist alternative configurations capable of matching or even surpassing this optimal value. Furthermore, an interesting consideration arises from the spatial proximity of the six producers. Given their close positioning, there is potential for aggregation into one or two total producers during the project's design phase. Consolidating these producers could streamline operational logistics and potentially optimize resource utilization, contributing to further efficiency gains.