Mechanistic Modeling of CO2 Migration in Heterogeneous Porous Media Using Wavelet-Assisted Damped Fractional Brownian Motion

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Abstract

Accurately modeling CO 2 diffusion in low-permeability heterogeneous reservoirs is critical for optimizing enhanced oil recovery and carbon sequestration strategies. We present a novel stochastic time series model that integrates damping effects, fractional Brownian motion, and wavelet transforms to simulate CO 2 migration and diffusion behavior in complex porous media. Compared to traditional approaches, our model captures multi-scale heterogeneity and dynamic fluctuations more effectively, offering improved predictive accuracy at microscopic spatial and temporal scales. This approach provides a refined understanding of CO 2 transport mechanisms in tight reservoirs and supports the design of more efficient CO 2 -EOR and CCUS operations.

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