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.

中文翻译：

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推进 CO2 地质封存的前沿：统计和计算视角


本讨论针对 Zhang 和 Arif 最近发表在《地球科学评论》上的关于地下地质 CO2 封存系统的残余捕获能力的系统综述。该讨论强调了残余捕集在确保长期 CO2 封存方面的关键作用。该研究利用统计方法和计算机理论，研究了测量技术、影响因素和未来前景。确定了方法问题，例如对已发布数据集的依赖和对高级统计分析的需求。该讨论表明了研究中统计稳健性和计算机建模技术的改进。未来的方向包括将机器学习用于数据分析，以及增强仿真模型以更好地预测 CO2 封存。这项综合评估强调了严格的分析方法在推进 CO2 地质封存领域的重要性。