Development of Efficient X-Ray CT Image Segmentation Techniques for Quantitative Analysis of Phase Distributions and Flow Processes in Porous Media

开发高效的X射线CT图像分割技术，用于定量分析多孔MediaMarkus Tuller、Pavel Iassonov和Marcel Schaap中的相分布和流动过程。该奖项由2009年美国复苏和再投资法案(公共法律111-5)资助。非破坏性成像方法，如X射线计算机层析成像(CT)，提供了多孔材料内孔隙空间和流体分布的高分辨率3D表示。稳步提高的计算能力和更方便地使用工业和同步辐射X射线CT设施，推动了最近微孔介质研究的激增，目标从孔隙尺度上的流体和界面动力学的理论方面到实际应用，如(D)NAPL的传输和溶解。近年来，在改进CT技术、微尺度分析和流体动力学模拟方面投入了大量的努力和资源。然而，用于将灰度CT体积转换为离散形式的足够的图像分割方法的开发远远落后于允许定量描述孔隙空间特征以及随后对液体分布和流动过程进行建模的形式。初步研究表明，最初为光学字符识别、模式分析或医学研究开发的大多数有案可查的分割方法，当应用于多孔材料的X射线CT数据时，会产生非常不同的结果。此外，几乎没有商业或开源软件具有先进的图像分割功能，适合自动处理大型CT数据集。为了克服这些缺点，我们将确定最有前途的分割方法，并开发新的混合算法，以适应天然多孔介质的工业和同步辐射X射线CT数据。格子Boltzmann模拟将在X射线CT衍生的离散孔隙空间内与独立测量的水力特性进行比较，将指导开发过程。生成的算法将被合并到一个用户友好的、独立的、有良好文档记录的软件包中，并向科学界提供。

Development of Efficient X-Ray CT Image Segmentation Techniques for Quantitative Analysis of Phase Distributions and Flow Processes in Porous MediaMarkus Tuller, Pavel Iassonov and Marcel SchaapThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Nondestructive imaging methods such as X-Ray Computed Tomography (CT) yield high-resolution 3 D representations of pore space and fluid distribution within porous materials. Steadily increasing computational capabilities and easier access to industrial and synchrotron X Ray CT facilities have contributed to a recent surge in microporous media research with objectives ranging from theoretical aspects of fluid and interfacial dynamics at the pore-scale to practical applications such as (D)NAPL transport and dissolution. In recent years, significant efforts and resources have been devoted to improve CT technology, micro-scale analysis, and fluid dynamics simulations. However, the development of adequate image segmentation methods for conversion of grayscale CT volumes into a discrete form that permits quantitative characterization of pore space features and subsequent modeling of liquid distribution and flow processes is lacking far behind. A preliminary study revealed that most of the documented segmentation methods that were originally developed for optical character recognition, pattern analysis, or medical research yield vastly different results when applied to X-Ray CT data of porous materials. Furthermore, there is virtually no commercial or open-source software with advanced image segmentation capabilities suitable for automated processing of large CT data sets available.To overcome these shortcomings we will identify the most promising segmentation methods and develop new hybrid algorithms tailored to industrial and synchrotron X-Ray CT data of natural porous media. Lattice Boltzmann simulations within X-Ray CT-derived discretized pore space compared to independently measured hydraulic properties will guide the development process. The generated algorithms will be combined in a user-friendly, stand-alone, and well documented software package and made available to the scientific community.