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On Log Normal Distribution of Pore Structures by Using Fractal Theory

Lang Zhao-xin

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Abstract

Pore structures in reservoir rocks possess good fractal characters. The fractal dimension of pore structure can be used to quantitatively describe its complexity and variation. Its distribution accords with its log normal distribution. This paper establishes a fractal characterization method of probability density function of pore size distribution by applying fractal geometry principle, according to the fractal geometry model of pore distribution and capillary pressure curves, which allows the conventional qualitative description to turn into quantitative estimation of the pore sized distribution. The estimation shows that this method is easier for use and higher in accuracy.

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What this paper is about

Pore structures in reservoir rocks possess good fractal characters. The fractal dimension of pore structure can be used to quantitatively describe its complexity and variation. Its distribution accords with its log normal distribution. This paper establishes a fractal characterization method of probability density function of pore size distribution by applying fractal geometry principle, according to the fractal geometry model of pore distribution and capillary pressure curves, which allows the conventional qualitative description to turn into quantitative estimation of the pore sized distribution. The estimation shows that this method is easier for use and higher in accuracy.

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Available abstract

Pore structures in reservoir rocks possess good fractal characters. The fractal dimension of pore structure can be used to quantitatively describe its complexity and variation. Its distribution accords with its log normal distribution. This paper establishes a fractal characterization method of probability density function of pore size distribution by applying fractal geometry principle, according to the fractal geometry model of pore distribution and capillary pressure curves, which allows the conventional qualitative description to turn into quantitative estimation of the pore sized distribution. The estimation shows that this method is easier for use and higher in accuracy.

Key concepts: Fractal, Fractal dimension, Fractal dimension on networks, Geometry, Distribution (mathematics), Fractal analysis, Fractal derivative, Capillary pressure

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