Speaker
Description
Fractures act as highly conductive pathways, strongly influencing flow and transport in subsurface formations. Accurately modeling their effects is challenging due to the high uncertainty in fracture configurations. Monte Carlo simulations (MCS) are commonly used to estimate flow and transport behavior, but they are computationally expensive and subject to considerable uncertainties. To address both aspects, we recently proposed a statistical integro-differential fracture model (Sid-FM) that directly computes mean fields from fracture statistics, circumventing the need for MCS. The model employs kernel functions to represent expected flow exchange between fractures and the surrounding matrix and has been shown to reliably predict mean flow and pressure fields. In this work, we extend Sid-FM to scalar transport. We present the theoretical derivation of the governing equations, introduce new assumptions to close the covariance terms, and demonstrate good agreement with MCS results for statistically 1D test cases. The proposed framework provides a computationally efficient approach for simulating flow and transport in fractured porous media. Its extension to 2D and 3D scenarios positions it as a promising tool for subsurface engineering and environmental applications.
| Country | Switzerland |
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