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Content available remote Construction of pore network model based on computational geometry
EN
The digital core and pore network model (PNM) are the basis of studying porous media. At present, the voxel-based maximal ball (MB) method has been widely used in the construction of PNM. However, due to the dependence on discrete data and the fuzziness of size definition, the PNM by using this method may not be accurate. The construction of PNM is essentially a geometric problem. Therefore, a computational geometry method was proposed in this paper to construct the PNM. A grid-based core surface model was constructed by using the moving cubes (MC) algorithm, the maximal inscribed ball of the grid space was extracted by using the computational geometry method, and a PNM was built by judging 12 types of dependency relationships of the master and servant spheres in the inscribed ball. Finally, combined with Berea sandstone, the physical parameters of cores obtained by the proposed method and the MB method were compared. The throat length results show that the proposed algorithm has improved the defect of small throat length when the MB method is used to partition core pore space. Meanwhile, the results of other parameters tend to be consistent, which proves the reliability of the proposed algorithm. Besides, by comparing the seepage simulation results of the two methods with the physical experiments, it was proved that the permeability calculated by the method in this paper is closer to the measured value of the physical experiment than that by the MB method.
2
EN
Based on the three-dimensional digital core of Berea sandstone, three-phase (matrix, wet clay and free water) digital cores of clay-bearing sandstone are constructed. We divide clay into structural clay and dispersed clay according to the location where clay growth occurs. The fnite-element method is used to simulate the electrical characteristics of digital cores in order to study the relationship between the conductivity of core saturated with brine (C0) and the brine conductivity (Cw). The infuence of clay mineral type, content and porosity on core electrical characteristics is taken into account. The results show that the additional conductivity is related to the clay minerals, and montmorillonite has the highest cation exchange capacity, resulting in the largest additional conductivity. The increase in clay content in cores increases the conductivity of core C0. At the same time, clay that flls pores decreases the porosity and causes the decrease in C0. These are two opposing factors of conductivity that coexist in clay-bearing sandstone.
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