# Optimization of Offshore Saline Aquifer CO2 Storage in Smeaheia Using Surrogate Reservoir Models
## 6 Conclusions  
This study examined fast simulation and optimization of CO\({}_{2}\) storage in Smeaheia aquifer through the utilization of grid-based proxy models. Furthermore, the work addressed several challenges that arise in the development and application of such SRMs. In brief:  
1. In this work, a non-cascading grid-based SRM was deemed appropriate for long-term surrogate reservoir modeling and optimization in the context of Smeaheia storage.
2. Proxy models built for replicating both CO\({}_{2}\) saturation and pressure data showed excellent accuracy compared with the results of the numerical simulator. Data sampling for the former could be conducted by assessing the degree of property fluctuation over time, as opposed to pressure data, which necessitates random samples.
3. The pressure SRM exhibited less than 0.5% error, which shows its applicability in future studies, especially when it comes to coupling it with geomechanical models.
4. To effectively tackle the issue of accumulated error at the CO2 plume boundary when SRM is applied at high injection rates, it is recommended to use higher maximum injection rates that exceed the maximum rate for model application in the training phase.
5. By leveraging the SRMs, an optimization process consisting of 10,000 iterations was successfully completed within a time frame of 50 min, achieved by constraining the simulation volume. This is a huge reduction in computational time compared with optimization using the numerical model.
6. Finally, the study demonstrated that CO2 can be injected in Smeaheia at a rate of around 3.4 Mt per year to safely store about 170 Mt CO2 in 50 years.  
Regarding the limitations of this study, SRMs are limited in generalizing to different geological contexts (i.e., fit-for-purpose rather than one-size-fits-all). In order to utilize SRMs for simulating a different reservoir, it is necessary to retrain the models, as per the standard approach of proxy modeling. Non-cascading SRMs offer advantages in modeling CO2 storage; nevertheless, they are impaired in post-injection simulation due to the fact that the developed SRMs cannot accurately predict the final time step of the CO2 injection. To make a post-injection prediction, it is necessary to either train an additional SRM or retrain the current SRMs with a more extended network and additional input and output features. Furthermore, a deterministic approach was employed in this study, neglecting geological uncertainty. Also, since there is no historical data available for the project, the numerical model being used is not history matched. These limitations need to be addressed in a computationally efficient manner in future studies.  
Conceptualization, B.A., A.J.G., V.R. and C.S.W.N.; Data curation, B.A.; Formal analysis, A.J.G.; Funding acquisition, B.A.; Investigation, B.A.; Methodology, B.A.; Software, B.A.; Supervision, A.J.G. and V.R.; Validation, C.S.W.N.; Writing--original draft, B.A.; Writing--review and editing, A.J.G., V.R. and C.S.W.N. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Politecnico di Torino [grant number 1490 of 1 October 2021] in a mobility program, and EDISU in International Mobility 2022 program.  
The dataset employed in this study is an open-source data from [https://co2 datashare.org/dataset/smeaheia-dataset](https://co2 datashare.org/dataset/smeaheia-dataset) (accessed on 23 February 2021), and all rights are possessed by Equinor and Gassnova.  
The project was conducted at Politecnico di Torino and CEORS Gemini-Center (CO2 Enhanced Oil Recovery and Storage), a strategic collaboration between NTNU and SINTEF ([[https://www.ntnu.edu/ceors](https://www.ntnu.edu/ceors)]([https://www.ntnu.edu/ceors](https://www.ntnu.edu/ceors))). The authors acknowledge the feedback and suggestions by [PERSON] (Equinor) and [PERSON] (SINTEF).  
The authors have no competing interests to declare that are relevant to the content of this article.