X-ray microcomputed tomography (X-ray μ -CT) is a rapidly advancing technology that has been successfully employed to study flow phenomena in porous media. It offers an alternative approach to core scale experiments for the estimation of traditional petrophysical properties such as porosity and single-phase flow permeability. It can also be used to investigate properties that control multiphase flow such as rock wettability or mineral topology. In most applications, analyses are performed on segmented images obtained employing a specific processing pipeline on the greyscale images. The workflow leading to a segmented image is not straightforward or unique and, for most of the properties of interest, a ground truth is not available. For this reason, it is crucial to understand how image processing choices control properties estimation. In this work, we assess the sensitivity of porosity, permeability, specific surface area, in situ contact angle measurements, fluid–fluid interfacial curvature measurements and mineral composition to processing choices. We compare the results obtained upon the employment of two processing pipelines: non-local means filtering followed by watershed segmentation; segmentation by a manually trained random forest classifier. Single-phase flow permeability, in situ contact angle measurements and mineral-to-pore total surface area are the most sensitive properties, as a result of the sensitivity to processing of the phase boundary identification task. Porosity, interfacial fluid–fluid curvature and specific mineral descriptors are robust to processing. The sensitivity of the property estimates increases with the complexity of its definition and its relationship to boundary shape.

中文翻译：

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多孔岩多相流体和固体性质估计对图像处理的敏感性

X 射线显微计算机断层扫描 (X-ray μ-CT) 是一项快速发展的技术，已成功用于研究多孔介质中的流动现象。它为岩心尺度实验提供了一种替代方法，用于估计孔隙度和单相流渗透率等传统岩石物理特性。它还可以用于研究控制多相流的特性，例如岩石润湿性或矿物拓扑。在大多数应用程序中，对灰度图像采用特定处理管道获得的分割图像进行分析。导致分割图像的工作流程并不简单或独特，并且对于大多数感兴趣的属性，基本事实不可用。因此，了解图像处理选择如何控制属性估计至关重要。在这项工作中，我们评估孔隙度、渗透率、比表面积、原位接触角测量、流体-流体界面曲率测量和矿物成分对加工选择的敏感性。我们比较了在使用两个处理管道时获得的结果：非局部均值过滤，然后是分水岭分割；通过手动训练的随机森林分类器进行分割。由于对相界识别任务处理的敏感性，单相流渗透率、原位接触角测量和矿物到孔隙的总表面积是最敏感的特性。孔隙率、界面流体-流体曲率和特定的矿物描述符对加工具有鲁棒性。