2022/02/17 by Karim Makki, Jean François Lecomte, Makki, Karim +8
Computer Science · Economics, Econometrics and Finance · Engineering · #Anomaly Detection Techniques and Applications #Complex Systems and Time Series Analysis #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Time Series Analysis and Forecasting #cs.CV #eess.IV #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2202.08717
arxiv created 2022/02/17 · openalex publication_date 2022/02/17 · arxiv updated 2022/02/18 · openalex created_date 2022/04/03 · openalex updated_date 2026/07/28
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.