Fractal Dynamics Modeling of Spatiotemporal Pore Structure Evolution in Tight Reservoirs

In this study, we propose a dynamic fractal dimension modeling (DFDM) framework that integrates image analysis, wavelet-based fractal methods, and structural fractal geometry to quantify the evolution of pore complexity. Unlike conventional static fractal approaches, our method captures time-dependent scaling laws and captures the spatiotemporal evolution of pore networks. The results demonstrate that dynamic fractal dimensions provide a robust descriptor of multi-scale heterogeneity, effectively bridging pore-scale processes with reservoir-scale behavior. This framework not only advances the theoretical understanding of fractal pore dynamics but also establishes a predictive tool with potential applications in unconventional hydrocarbon recovery, geological CO2 sequestration, and multi-phase flow in porous media.