Abstract

Fractures are common in carbonate formations, and it is challenging to characterize electrical properties and establish saturation models for the fractured rocks by conventional petrophysical experiments. Therefore, it is necessary to study the fractures' electrical conduction and establish water saturation models by pore-scale numerical simulation and microscopic analyses. First, a multi-composition digital rock is constructed by the X-ray CT scan, Maps, and quantitative evaluation of minerals by scanning electron microscopy multi-scale supporting experiments. Next, the fractal Brown motion is used to construct the fractured digital rocks, and the lattice Boltzmann method is used to simulate the oil-water distribution. Then, the resistivities of these digital rocks are calculated by the finite element method. Finally, the microscopic response mechanism of the electrical properties is studied in detail, and new water saturation models are established. The study shows that resistivity decreases as the fracture aperture, length, or quantities increase. Still, it has different changes in three directions with the rise of the fracture dip, indicating the fractures lead to electrical anisotropy of the rock. Additionally, the resistivity index (RI) is strongly correlated to the water saturation (Sw). In the highly water-saturated region, the RI-Sw curve conforms to Archie's law. However, the RI-Sw curve bends in the lowly water-saturated region, revealing the so-called ‘non-Archie’ behavior. Hence, we established new saturation models for fractured carbonate rocks and use one of the saturation models to calculate water saturation for formation evaluation in Tahe Oilfield. The calculated results are more consistent with the oil test results, demonstrating the proposed saturation model is more applicable in the fractured formation. In summary, the pore-scale numerical simulation in fractured carbonate rocks provides a microscopic theoretical basis for electrical mechanism analysis and a water saturation model for log interpretation.

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