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Probabilistic modeling and global sensitivity analysis for CO 2 storage in geological formations: a spectral approach

机译:地质构造中CO 2储存的概率建模和整体敏感性分析:一种光谱方法

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摘要

This work focuses on the simulation of CO2 storage in deep underground formations under uncertainty and seeks to understand the impact of uncertainties in reservoir properties on CO2 leakage. To simulate the process, a non-isothermal two-phase two-component flow system with equilibrium phase exchange is used. Since model evaluations are computationally intensive, instead of traditional Monte Carlo methods, we rely on polynomial chaos (PC) expansions for representation of the stochastic model response. A non-intrusive approach is used to determine the PC coefficients. We establish the accuracy of the PC representations within a reasonable error threshold through systematic convergence studies. In addition to characterizing the distributions of model observables, we compute probabilities of excess CO2 leakage. Moreover, we consider the injection rate as a design parameter and compute an optimum injection rate that ensures that the risk of excess pressure buildup at the leaky well remains below acceptable levels. We also provide a comprehensive analysis of sensitivities of CO2 leakage, where we compute the contributions of the random parameters, and their interactions, to the variance by computing first, second, and total order Sobol’ indices.
机译:这项工作的重点是在不确定性下模拟深地下地层中的CO2储存,并试图了解储层性质的不确定性对CO2泄漏的影响。为了模拟该过程,使用了具有平衡相交换的非等温两相两组分流动系统。由于模型评估是计算密集型的,而不是传统的蒙特卡洛方法,因此我们依靠多项式混沌(PC)展开来表示随机模型响应。非介入方法用于确定PC系数。通过系统的收敛性研究,我们在合理的误差阈值内建立了PC表示的准确性。除了表征模型可观察物的分布之外,我们还计算出过量CO2泄漏的概率。此外,我们将注入速率视为设计参数,并计算最佳注入速率,以确保泄漏井中过高压力累积的风险保持在可接受水平以下。我们还提供了对CO2泄漏敏感性的综合分析,其中我们通过计算一阶,二阶和总阶Sobol指数来计算随机参数及其相互作用对方差的贡献。

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