标题： 利用三维数字阴影技术推进地质碳封存监测 显示英文标题

标题： Advancing Geological Carbon Storage Monitoring With 3d Digital Shadow Technology

摘要： 地质碳储存（GCS）是一种通过将二氧化碳封存于深层地质构造中以实现全球气候目标的关键技术。 其效果和安全性依赖于使用先进的时移地震成像技术对地下二氧化碳迁移进行准确监测。 数字镜像框架整合现场数据，包括地震和钻孔测量数据，以跟踪随时间变化的二氧化碳饱和度。 机器学习辅助的数据同化技术，如生成式人工智能和非线性集合贝叶斯过滤，能够在考虑储层特性不确定性的同时更新二氧化碳羽流的数字模型。 与二维方法相比，三维监测提高了GCS评估的空间准确性，能够捕捉二氧化碳迁移的全部范围。 本研究通过引入三维地震成像和储层建模，扩展了具有不确定性感知的二维数字镜像框架，从而在二氧化碳储存项目中提高了决策能力和风险缓解效果。 显示英文摘要

摘要： Geological Carbon Storage (GCS) is a key technology for achieving global climate goals by capturing and storing CO2 in deep geological formations. Its effectiveness and safety rely on accurate monitoring of subsurface CO2 migration using advanced time-lapse seismic imaging. A Digital Shadow framework integrates field data, including seismic and borehole measurements, to track CO2 saturation over time. Machine learning-assisted data assimilation techniques, such as generative AI and nonlinear ensemble Bayesian filtering, update a digital model of the CO2 plume while incorporating uncertainties in reservoir properties. Compared to 2D approaches, 3D monitoring enhances the spatial accuracy of GCS assessments, capturing the full extent of CO2 migration. This study extends the uncertainty-aware 2D Digital Shadow framework by incorporating 3D seismic imaging and reservoir modeling, improving decision-making and risk mitigation in CO2 storage projects.