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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的概率模型和整体敏感性分析：一种光谱方法

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摘要

This work focuses on the simulation of CO_2 storage in deep underground formations under uncertainty and seeks to understand the impact of uncertainties in reservoir properties on CO_2 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 CO_2 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 CO_2 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层地下CO_2的储存，并试图了解储层特性不确定性对CO_2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外，我们还计算出过量CO_2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CO_2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对变量和方差的贡献。

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  • 来源
    《Applied Mathematical Modelling》 |2018年第1期|584-601|共18页
  • 作者

    Bilal M. Saad; Alen Alexanderian; Serge Prudhomme; Omar M. Knio;

  • 作者单位

    Division of Computer, Electrical and Mathematical Sciences & Engineering, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal 23955-6900, Kingdom of Saudi Arabia,The Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA;

    Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA;

    Departement de mathematiques et de genie Industriel, Ecole Polyrechnique de Montreal C.P. 6079, succ. Centre-ville, Montreal, Quebec,Canada H3C 3A7;

    Division of Computer, Electrical and Mathematical Sciences & Engineering, King Abdullah University of Science and Technology, 4700 KAUST, Thuwal 23955-6900, Kingdom of Saudi Arabia,Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Carbon sequestration; Multiphase flow; Risk assessment; Parametric uncertainty; Polynomial chaos; Sensitivity analysis;

    机译：碳汇;多相流;风险评估;参数不确定性;多项式混沌敏感性分析;

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