Advancing the frontiers of CO2 geological storage: A statistical and computational perspective

Abstract

This discussion addresses a recent systematic review by Zhang and Arif on the residual trapping capacity of subsurface systems for geological CO₂ storage, published in Earth-Science Reviews. The discussion highlights the critical role of residual trapping in ensuring long-term CO₂ sequestration. Utilizing statistical methods and computer theory, the study examines measurement techniques, influencing factors, and future prospects. Methodological concerns, such as reliance on published datasets and the need for advanced statistical analyses, are identified. The discussion suggests improvements in statistical robustness and computer modeling techniques in research. Future directions include incorporating machine learning for data analysis and enhancing simulation models for better CO₂ storage predictions. This comprehensive evaluation underscores the significance of rigorous analytical methods in advancing the field of CO₂ geological storage.