Abstract

Characterizing internal microscopic structures of porous media is of vital importance to simulate fluid and electric current flow. Compared to traditional rock mechanics and geophysical experiments, digital core and pore network modeling is attracting more interests as it can provide more details on rock microstructure with much less time needed. The axis extraction algorithm, which has been widely applied for pore network modeling, mainly consists of a reduction and burning algorithm. However, the commonly used methods in an axis extraction algorithm have the disadvantages of complex judgment conditions and relatively low operating efficiency, thus losing the practicality in application to large-scale pore structure simulation. In this paper, the updated algorithm proposed by Palágyi and Kuba was used to perform digital core and pore network modeling. Firstly, digital core was reconstructed by using the Markov Chain Monte Carlo (MCMC) method based on the binary images of a rock cutting plane taken from heavy oil reservoir sandstone. The digital core accuracy was verified by comparing porosity and autocorrelation function. Then, we extracted the central axis of the digital pore space and characterize structural parameters through geometric transformation technology and maximal sphere method. The obtained geometric parameters were further assigned to the corresponding nodes of pore and throat on the central axis of the constructed model. Moreover, the accuracy of the new developed pore network model was measured by comparing pore/throat parameters, curves of mercury injection, and oil-water relative permeability. The modeling results showed that the new developed method is generally effective for digital core and pore network simulation. Meanwhile, the more homogeneity of the rock, which means the stronger “representative” of binary map the rock cutting plane, the more accurate simulated results can be obtained.

Highlights

  • Porous media, such as metal, wood, soil, and rock, is one of the most common substances in daily life [1,2,3]

  • We developed a new method for digital core and core network modeling based on the algorithm proposed by Palágyi and Kuba and the Markov Chain Monte Carlo (MCMC) method

  • (1) The modeling results show that the digital core of heavy oil reservoir sandstone reconstructed with this digital core modeling method can accurately reflect the microstructure characteristics of the real core

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Summary

Introduction

Porous media, such as metal, wood, soil, and rock, is one of the most common substances in daily life [1,2,3]. Six deletion templates in the algorithm simplify the analysis of neighboring voxels, making this central axis method computationally effective While this method has been widely used in the study of heart and cerebral vessels [35,36,37] and pulmonary vessels [38, 39] of human, early embryonic mouse heart [40], and plants [41] and shows satisfactory results, to the best of our knowledge, it has not ever been applied petroleum engineering for core-scale pore network simulation

Traversed voxel
Methodology
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Conclusions
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