Abstract Pore-scale modeling is a rapidly evolving area of research because modeling multiphase flow directly on 3D pore geometries is of utmost importance in wide variety of research areas, including oil and gas development, hydrology and material sciences. Although there are numerous methods to model flow, only so-called pore-network models are computationally effective enough to perform simulations in large modeling domains, and they are orders of magnitude faster than direct modeling approaches. However, pore-network models require a simplification of the 3D pore geometry to perform simulations, which are usually referred to as pore-network extraction. Such extraction poses a separate problem because it must provide an accurate description of the pore space geometry and topology. Different methods have been proposed in the literature. Recently, watershed-based approaches have been popular due to their effectiveness in working with porous media images of any porosity. A watershed algorithm requires seed placement to segment the space into distinct pores. We propose a hybrid algorithm combining the power of watersheds in finding intersections between pores with the advantages of the maximum inscribed ball technique, which is very effective in finding pore centers. We rigorously verify and test our novel methodology on artificial and X-ray microtomography images of wide variety of porous materials: sphere packings, carbonate, soil, ceramic and sandstone samples. Comparison against a purely watershed-based method and results based solely on the maximum inscribed balls–based method (in terms of pore/throat total number, pore size distributions and connection statistics, and multiphase flow properties including capillary curves and relative permeabilities) revealed the accuracy of our novel technique, consistency with existing classical techniques and great potential in analysing 3D pore images of any complexity. On the other hand, comparison of extracted pore-network topology (as based on Euler number) revealed significant differences between different methodologies, which is rather surprising considering the similarities in two-phase flow properties. While analysing permeability results, we also compared two popular pore-throat partitioning models and advocated in favor of the weight model usually utilized within watershed-based extracted pore networks. Our results illuminate problems in current pore-network models and outline some potential ways to improve their accuracy in future research.

中文翻译：

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利用最大内接球孔体定位改进基于流域的孔网提取方法

摘要 孔隙尺度建模是一个快速发展的研究领域，因为直接在 3D 孔隙几何结构上建模多相流在石油和天然气开发、水文学和材料科学等广泛的研究领域至关重要。尽管有许多方法可以模拟流动，但只有所谓的孔隙网络模型在计算上足够有效，可以在大型建模域中执行模拟，并且它们比直接建模方法快几个数量级。然而，孔隙网络模型需要简化 3D 孔隙几何结构来执行模拟，这通常称为孔隙网络提取。这种提取提出了一个单独的问题，因为它必须提供对孔隙空间几何形状和拓扑结构的准确描述。文献中提出了不同的方法。最近，基于分水岭的方法因其在处理任何孔隙度的多孔介质图像方面的有效性而广受欢迎。分水岭算法需要放置种子以将空间分割成不同的孔隙。我们提出了一种混合算法，结合了分水岭寻找孔隙交叉点的能力和最大内接球技术的优点，在寻找孔隙中心方面非常有效。我们在各种多孔材料的人工和 X 射线显微断层扫描图像上严格验证和测试我们的新方法：球形填料、碳酸盐、土壤、陶瓷和砂岩样品。与纯粹基于分水岭的方法和仅基于最大内接球方法的结果进行比较（在孔/喉总数、孔径分布和连接统计方面，和多相流动特性，包括毛细管曲线和相对渗透率）揭示了我们新技术的准确性，与现有经典技术的一致性以及分析任何复杂 3D 孔隙图像的巨大潜力。另一方面，提取的孔隙网络拓扑结构（基于欧拉数）的比较揭示了不同方法之间的显着差异，考虑到两相流动特性的相似性，这是相当令人惊讶的。在分析渗透率结果的同时，我们还比较了两种流行的孔喉划分模型，并提倡通常在基于流域的提取孔隙网络中使用的权重模型。我们的结果阐明了当前孔隙网络模型中的问题，并概述了在未来研究中提高其准确性的一些潜在方法。