Results of the summarizing process for the arXiv paper: 2201.00669v2

The study presents an optimization procedure for sealing leakage paths using microbially induced calcite precipitation (MICP) in the context of CO$_2$ storage. The research utilizes a field-scale MICP mathematical model implemented in the industry-standard simulator Open Porous Media (OPM) Flow and employs the ensemble-based optimization (EnOpt) algorithm to solve the optimization problem. The objective function is designed to maximize calcite precipitation within the shortest possible MICP operational time. An innovative injection strategy is developed to efficiently produce calcite in and around the leakage paths while avoiding clogging unwanted areas of the reservoir, such as the near-well region. This strategy involves simultaneous injection of growth and cementation solutions in separate well segments to initiate the MICP process after establishing a biofilm in the leakage paths during an initial injection phase. The optimization procedure is applied to three synthetic CO$_2$ leakage scenarios, demonstrating its effectiveness in sealing leakage paths while minimizing total MICP operational time. The results show successful closure of leakage paths in all scenarios, highlighting the potential of this approach for mitigating CO$_2$ leakage risks. Additionally, economic considerations are incorporated into the optimization process by weighing calcite precipitation at leakage paths against total injection and no-flow time, ensuring cost-effective sealing of leakage paths. Overall, this study contributes valuable insights into optimizing injection strategies for field-scale application of MICP for leakage mitigation, showcasing its potential for enhancing CO$_2$ storage security and efficiency.

• Optimization procedure for sealing leakage paths using MICP in CO$_2$ storage context
• Utilization of field-scale MICP mathematical model in OPM Flow with EnOpt algorithm
• Objective function to maximize calcite precipitation in shortest operational time
• Innovative injection strategy to efficiently produce calcite while avoiding clogging unwanted areas
• Application of optimization procedure to three synthetic CO$_2 leakage scenarios, demonstrating effectiveness
• Successful closure of leakage paths in all scenarios, highlighting potential for mitigating CO$_2 leakage risks
• Incorporation of economic considerations into optimization process for cost-effective sealing of leakage paths

Introduction

The increasing concentration of carbon dioxide (CO$_2$) in the atmosphere due to human activities has led to concerns about its impact on climate change. One potential solution for mitigating CO$_2$ emissions is through carbon capture and storage (CCS), where CO$_2$ is captured from industrial sources and stored in geological formations deep underground. However, one of the major risks associated with CCS is the potential leakage of stored CO$_2$ back into the atmosphere, which could undermine its effectiveness as a mitigation strategy.

To address this issue, researchers have been exploring various methods for sealing leakage paths in geological formations. One promising approach is microbially induced calcite precipitation (MICP), where bacteria are used to precipitate calcium carbonate (calcite) in porous media, effectively sealing any pathways for fluid flow. This method has shown great potential for sealing leakage paths in laboratory experiments, but its application at field-scale remains a challenge.

In this context, a recent research paper titled "Optimization of Microbially Induced Calcite Precipitation for Sealing Leakage Paths during CO$_2$ Storage" presents an innovative optimization procedure for applying MICP at field-scale to mitigate CO$_2$ leakage risks. The study utilizes a combination of mathematical modeling and optimization techniques to design an efficient injection strategy that maximizes calcite precipitation while minimizing operational time and costs.

Field-Scale MICP Mathematical Model

The first step in this study was developing a field-scale MICP mathematical model using the industry-standard simulator Open Porous Media (OPM) Flow. The model considers key factors such as bacterial growth kinetics, biofilm formation, transport processes, and chemical reactions involved in MICP. It also accounts for heterogeneity and anisotropy of the reservoir by incorporating geologic data from real-world sites.

Ensemble-Based Optimization Algorithm

Once the mathematical model was developed, it was coupled with an ensemble-based optimization (EnOpt) algorithm to solve the optimization problem. EnOpt is a powerful technique that uses an ensemble of simulations to find the optimal solution, making it suitable for complex and uncertain systems like CO$_2$ storage.

Objective Function and Injection Strategy

The objective function in this study was designed to maximize calcite precipitation within the shortest possible MICP operational time. To achieve this, an innovative injection strategy was developed, which involves simultaneous injection of growth and cementation solutions in separate well segments. This approach allows for the establishment of a biofilm in leakage paths during an initial injection phase before initiating the MICP process.

Application to Synthetic Leakage Scenarios

To demonstrate the effectiveness of this optimization procedure, it was applied to three synthetic CO$_2$ leakage scenarios with varying degrees of complexity. The results showed successful closure of leakage paths in all scenarios, highlighting the potential of this approach for mitigating CO$_2$ leakage risks at field-scale.

Incorporating Economic Considerations

In addition to optimizing calcite precipitation and operational time, economic considerations were also incorporated into the optimization process. This involved weighing calcite precipitation at leakage paths against total injection and no-flow time, ensuring cost-effective sealing of leakage paths.

Conclusion

Overall, this research paper presents a comprehensive study on optimizing MICP for sealing leakage paths during CO$_2$ storage. By combining mathematical modeling with an ensemble-based optimization algorithm, an efficient injection strategy was developed that maximizes calcite precipitation while minimizing operational time and costs. The results from synthetic scenarios demonstrate its potential for field-scale application in mitigating CO$_2$ leakage risks. Incorporating economic considerations further enhances its practicality as a mitigation strategy for CCS projects. This study contributes valuable insights into optimizing MICP strategies for enhancing CO$_2$ storage security and efficiency.