论文标题
由光流驱动的基于水平集的粒子滤波器：从X射线CT时间序列跟踪盐边界的应用
Level set based particle filter driven by optical flow: an application to track the salt boundary from X-ray CT time-series
论文作者
论文摘要
长期以来，基于图像的计算流体动力学在利用知识和对几种物理现象的理解中发挥了重要作用。特别是，概率计算方法为在纯粹随机湍流运动中的复杂动力学建模开辟了道路。在结构地质学领域，对盐和周围岩石内的变形和应力状态的更好理解都非常有趣，可以表征各种地下长期能量存储系统。这项研究的目的是使用X射线计算机断层扫描（CT）图像时间序列的平行的随机滤波方法来确定盐边界随时间推移的非线性变形，这些方法描述了由重力触发的盐结构的演变，并在不同的负载下触发了盐结构的演变。这项工作是将物理建模和高级随机图像处理方法汇总在一起的第一步，其中考虑了模型不确定性。
Image-based computational fluid dynamics have long played an important role in leveraging knowledge and understanding of several physical phenomena. In particular, probabilistic computational methods have opened the way to modelling the complex dynamics of systems in purely random turbulent motion. In the field of structural geology, a better understanding of the deformation and stress state both within the salt and the surrounding rocks is of great interest to characterize all kinds of subsurface long-terms energy-storage systems. The objective of this research is to determine the non-linear deformation of the salt boundary over time using a parallelized, stochastic filtering approach from x-ray computed tomography (CT) image time series depicting the evolution of salt structures triggered by gravity and under differential loading. This work represents a first step towards bringing together physical modeling and advanced stochastic image processing methods where model uncertainty is taken into account.
