Impacts of permeability heterogeneities on foam flow in porous media: Uncertainty quantification and sensitivity analysis

0 ENERGY & FUELS
Berilo de Oliveira Santos , Rodrigo Weber dos Santos , Iury Igreja , Grigori Chapiro , Bernardo Martins Rocha
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引用次数: 0

Abstract

Foam injection in porous media has been extensively studied for its ability to improve sweep efficiency by mitigating nonlinear phenomena such as gravitational segregation and viscous fingering. However, modeling foam flow remains a significant challenge, mainly due to the complex interactions between foam and heterogeneous geological formations, which are often difficult to characterize. In particular, the spatial distribution of absolute permeability is difficult to obtain, due to scarce data and strong heterogeneity. These challenges introduce uncertainties into predictive models. In particular, the relationship between foam flow and uncertainties related to absolute permeability fields remains underexplored in the literature. This work performs uncertainty propagation studies to investigate the influence of permeability heterogeneity on foam flow in porous media. This is achieved by coupling the Karhunen-Loève expansion (KLE), which generates Gaussian random permeability fields, with Polynomial Chaos Expansion (PCE), a method for propagating uncertainties in a computationally efficient manner. This approach allows for the evaluation of permeability variations impact on key quantities of interest (QoIs) related to flow performance. The results, derived from uncertainty quantification (UQ) and sensitivity analysis (SA), reveal that foam behavior is highly sensitive to the spatial correlation structures of permeability, with important implications for optimizing foam flow processes. The integration of KLE and PCE provides the first systematic framework for uncertainty propagation in foam flow analysis, unveiling previously unexplored correlations and behaviors. These findings highlight the importance of incorporating permeability uncertainties into modeling to improve the reliability and efficiency of both subsurface flow applications, including resource recovery and carbon sequestration efforts. The proposed methodology can be particularly beneficial in practical scenarios such as enhanced oil recovery or CO2 sequestration, where foam is used to improve mobility control in complex formations.
渗透率非均质性对多孔介质泡沫流动的影响:不确定度量化和敏感性分析
多孔介质中的泡沫注入能够通过减轻重力偏析和粘指现象等非线性现象来提高波及效率,因此得到了广泛的研究。然而,泡沫流动建模仍然是一个重大挑战,主要是由于泡沫和非均质地质构造之间复杂的相互作用,往往难以表征。特别是,由于数据稀缺,非均质性强,难以获得绝对渗透率的空间分布。这些挑战为预测模型引入了不确定性。特别是,泡沫流动与绝对渗透率场的不确定性之间的关系在文献中仍未得到充分探讨。本文通过不确定性传播研究来探讨渗透率非均质性对多孔介质泡沫流动的影响。这是通过将karhunen - lo展开(KLE)与多项式混沌展开(PCE)耦合来实现的,后者产生高斯随机磁导率场,而多项式混沌展开(PCE)是一种以计算效率高的方式传播不确定性的方法。这种方法可以评估渗透率变化对与流动性能相关的关键感兴趣量(qoi)的影响。不确定性量化(UQ)和敏感性分析(SA)的结果表明,泡沫行为对渗透率的空间相关结构高度敏感,这对泡沫流动过程的优化具有重要意义。KLE和PCE的集成为泡沫流分析中的不确定性传播提供了第一个系统框架,揭示了以前未探索的相关性和行为。这些发现强调了将渗透率不确定性纳入建模的重要性,以提高地下流体应用的可靠性和效率,包括资源回收和碳封存工作。该方法在提高采收率或二氧化碳封存等实际应用中特别有用,在这些应用中,泡沫可以用于改善复杂地层的流动性控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
11.20
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