Pore Geometry Characterization by Persistent Homology Theory

研究成果: ジャーナルへの寄稿記事

抄録

Rock pore geometry has heterogeneous characteristics and is scale dependent. This feature in a geological formation differs significantly from artificial materials and makes it difficult to predict hydrologic and elastic properties. To characterize pore heterogeneity, we propose an evaluation method that exploits the recently developed persistent homology theory. In the proposed method, complex pore geometry is first represented as sphere cloud data using a pore-network extraction method. Then, a persistence diagram (PD) is calculated from the point cloud, which represents the spatial distribution of pore bodies. A new parameter (distance index H) derived from the PD is proposed to characterize the degree of rock heterogeneity. Low H value indicates high heterogeneity. A new empirical equation using this index H is proposed to predict the effective elastic modulus of porous media. The results indicate that the proposed PD analysis is very efficient for extracting topological feature of pore geometry.
元の言語英語
ページ(範囲)4150-4163
ページ数14
ジャーナルWater Resources Research
54
発行部数6
出版物ステータス出版済み - 2018

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homology
persistence
diagram
geometry
elastic property
elastic modulus
extraction method
rock
porous medium
spatial distribution
index

これを引用

Pore Geometry Characterization by Persistent Homology Theory. / Jiang, Fei; Tsuji, Takeshi; Shirai, Tomoyuki.

:: Water Resources Research, 巻 54, 番号 6, 2018, p. 4150-4163.

研究成果: ジャーナルへの寄稿記事

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AB - Rock pore geometry has heterogeneous characteristics and is scale dependent. This feature in a geological formation differs significantly from artificial materials and makes it difficult to predict hydrologic and elastic properties. To characterize pore heterogeneity, we propose an evaluation method that exploits the recently developed persistent homology theory. In the proposed method, complex pore geometry is first represented as sphere cloud data using a pore-network extraction method. Then, a persistence diagram (PD) is calculated from the point cloud, which represents the spatial distribution of pore bodies. A new parameter (distance index H) derived from the PD is proposed to characterize the degree of rock heterogeneity. Low H value indicates high heterogeneity. A new empirical equation using this index H is proposed to predict the effective elastic modulus of porous media. The results indicate that the proposed PD analysis is very efficient for extracting topological feature of pore geometry.

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