An improved method for predicting permeability by combining electrical measurements and mercury injection capillary pressure data

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Abstract

The applicability of the representative elemental volume (REV) model is analyzed on the basis of the capillary pressure curves, resistivity, porosity and permeability, taken from the experimental measurement data of 83 sandstone core samples from three different blocks mined in China. The results show that the permeability error (the ratio of core permeability to the permeability calculated by the REV model) can be controlled from 0.5 to 2 when the core permeability is more than 3 mD. On the whole, the permeability error is more than 2, and the calculated permeability is lower than the core permeability when the core permeability is less than 3 mD. The reason for the poor calculation accuracy of the REV model in low permeability sandstone is analyzed, and the research suggests that the ∫dSv/(Pc)2 in the REV model characterizes the pore-throat radius of the rock. In reality, the permeability is influenced by the throat radius rather than the pore radius. When the core permeability is large enough, there is no obvious difference between the pore radius and the throat radius. So, the error between the core permeability and the permeability calculated by the REV model is small. However, when the core permeability is small, the difference between the pore radius and the throat radius is apparent, and, in general, the pore radius is larger than the throat radius. In these conditions, the pore radius plays a leading role in ∫dSv/(Pc)2, thus making the error between the core permeability and the permeability calculated by the REV model apparent. Based on the above, we have derived an improved REV model by introducing the pore-throat radius ratio on the basis of Poiseuille's law and Darcy's law. Using the same experimental data, we make a comparison analysis between the improved model, the REV model and the Swanson model. The results show that compared with the REV model and the Swanson model, the accuracy of the calculated permeability of the improved model is obviously enhanced.

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Zhang, C., Cheng, Y., & Zhang, C. (2017). An improved method for predicting permeability by combining electrical measurements and mercury injection capillary pressure data. Journal of Geophysics and Engineering, 14(1), 132–142. https://doi.org/10.1088/1742-2140/14/1/132

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