Data Science at Scale Division, (CCS-7), Los Alamos National Laboratory, Los Alamos, NM.
Earth and Environmental Sciences Division, (EES-16), Los Alamos National Laboratory, Los Alamos, NM.
IEEE Trans Vis Comput Graph. 2017 Aug;23(8):1896-1909. doi: 10.1109/TVCG.2016.2582174. Epub 2016 Jun 20.
We present an analysis and visualization prototype using the concept of a flow topology graph (FTG) for characterization of flow in constrained networks, with a focus on discrete fracture networks (DFN), developed collaboratively by geoscientists and visualization scientists. Our method allows users to understand and evaluate flow and transport in DFN simulations by computing statistical distributions, segment paths of interest, and cluster particles based on their paths. The new approach enables domain scientists to evaluate the accuracy of the simulations, visualize features of interest, and compare multiple realizations over a specific domain of interest. Geoscientists can simulate complex transport phenomena modeling large sites for networks consisting of several thousand fractures without compromising the geometry of the network. However, few tools exist for performing higher-level analysis and visualization of simulated DFN data. The prototype system we present addresses this need. We demonstrate its effectiveness for increasingly complex examples of DFNs, covering two distinct use cases - hydrocarbon extraction from unconventional resources and transport of dissolved contaminant from a spent nuclear fuel repository.
我们提出了一个使用流拓扑图(FTG)概念的分析和可视化原型,用于描述约束网络中的流,重点是离散裂缝网络(DFN),由地质科学家和可视化科学家共同开发。我们的方法允许用户通过计算统计分布、分段感兴趣的路径以及根据路径对粒子进行聚类,来理解和评估 DFN 模拟中的流动和传输。这种新方法使领域科学家能够评估模拟的准确性、可视化感兴趣的特征,并在特定感兴趣的区域上比较多个实现。地质科学家可以模拟包含数千个裂缝的大型网络的复杂传输现象,而不会影响网络的几何形状。然而,很少有工具可用于对模拟的 DFN 数据进行更高级别的分析和可视化。我们提出的原型系统满足了这一需求。我们展示了它在越来越复杂的 DFN 示例中的有效性,涵盖了两个不同的用例——从非常规资源中提取碳氢化合物和从乏核燃料库中运输溶解污染物。