Fractal permeability model for gas flow in porous media with random asymmetric tortuous fracture network

Tree-like branching networks are ubiquitous in nature and engineering fields. Due to their self-similar fractal characteristics, they show unique advantages in the transport process. However, most of the existing research studies on the gas flow in the transition zone are limited to the symmetric case, and the possible effects of structural asymmetry are not taken into account. Therefore, the gas permeability model of a random distributed rough tree-like branching network with an asymmetric parallel plate structure is constructed based on fractal theory. By using the cubic law, the impact mechanism of various structural parameters on permeability was analyzed. Comparisons with experimental data and numerical simulation results indicate that the model's predicted relationship between gas flow rate and pressure difference has an error of less than 6% compared to the traditional symmetric model. Especially under high-pressure conditions, it matches more closely with the actual flow resistance characteristics than the symmetric model. This enriches the theory of gas flow in fractal porous media and highlights the significant impact of the asymmetric structural parameters of the dendritic branch network on gas permeability. It provides new theoretical support for understanding and predicting gas transport in complex porous media.

Authors

Institutions

Publication Details

Journal
Journal of Applied Physics
Published
2025-07-16
DOI
https://doi.org/10.1063/5.0278267
Primary Topic
Hydraulic Fracturing and Reservoir Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fractal permeability model for gas flow in porous media with random asymmetric tortuous fracture network

Shanshan Yang, Ruijuan Chen, Qian Zheng, Zihang Wu
Journal of Applied Physics
Hydraulic Fracturing and Reservoir Analysis
article

Fractal permeability model for gas flow in porous media with random asymmetric tortuous fracture network

Shanshan Yang, Ruijuan Chen, Qian Zheng, Zihang Wu
article en

Abstract

Tree-like branching networks are ubiquitous in nature and engineering fields. Due to their self-similar fractal characteristics, they show unique advantages in the transport process. However, most of the existing research studies on the gas flow in the transition zone are limited to the symmetric case, and the possible effects of structural asymmetry are not taken into account. Therefore, the gas permeability model of a random distributed rough tree-like branching network with an asymmetric parallel plate structure is constructed based on fractal theory. By using the cubic law, the impact mechanism of various structural parameters on permeability was analyzed. Comparisons with experimental data and numerical simulation results indicate that the model's predicted relationship between gas flow rate and pressure difference has an error of less than 6% compared to the traditional symmetric model. Especially under high-pressure conditions, it matches more closely with the actual flow resistance characteristics than the symmetric model. This enriches the theory of gas flow in fractal porous media and highlights the significant impact of the asymmetric structural parameters of the dendritic branch network on gas permeability. It provides new theoretical support for understanding and predicting gas transport in complex porous media.

Journal of Applied PhysicsVol. 138(3)
Wuhan Textile University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 83%
Hydraulic Fracturing and Reservoir Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.