Uncertainty quantification through reduced modelling of CO2 injection sites

通过减少二氧化碳注入点的建模来量化不确定性

• 批准号: 2596979
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2596979
• 关键词: Uncertainty; quantification; through; reduced; modelling

The project involves building on other work to model how to create physically meaningful models of the long-thin flows of CO2 (gravity currents) that naturally occur when storing CO2. This will involve grappling with the inherent heterogeneities within geological formations, with processes like dissolution which happen on a variety of length scales, and with the complex multi-phase flow of CO2 which can lead to trapping by surface tension. Simplified models will be used to identify the dominant physical processes. This PhD project looks to both understand those reduced physics models and then to utilise this computational efficiency to understand the sensitivity to the unknowns inthe problem, chiefly the geological reservoir itself. An additional aim is to understand how far CO2 might propagate from the injection point, which is sensitively dependent on the underlying geology. Viewing this more in a probabilistic sense, how far might we expect the CO2 to progress can be addressed using a simplified, gravity current model for the CO2 while using a more statistical representation of the underlying geology to give predictive maps of the risk of CO2 propagating a certain distance.

该项目包括在其他工作的基础上建立模型，如何创建有物理意义的长而薄的二氧化碳流（重力流）模型，这是储存二氧化碳时自然产生的。这将涉及到地质构造内部固有的非均质性、发生在不同长度尺度上的溶解等过程，以及复杂的二氧化碳多相流动，这可能会导致表面张力的捕获。简化模型将用于确定主要的物理过程。这个博士项目既要理解这些简化的物理模型，又要利用这种计算效率来理解问题中未知因素的敏感性，主要是地质储层本身。另一个目标是了解二氧化碳可能从注入点传播多远，这取决于潜在的地质情况。从概率的角度来看，我们可以用一个简化的二氧化碳重力流模型来计算二氧化碳传播的距离，同时用一个更统计的底层地质表示来给出二氧化碳传播一定距离的风险预测图。