Weibiao Xie
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Weibiao Xie has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Jianbin Zhao
Geology Research Institute, China National Logging Corporation
1 shared publication - Jingbo Zeng
China Petroleum Logging Co., Ltd., Xi’an 710000, China
1 shared publication - Pan Zhang
School of Petroleum, China University of Petroleum (Beijing) at Karamay, Karamay 834000, China
1 shared publication - Qiuli Yin
School of Petroleum, China University of Petroleum (Beijing) at Karamay, Karamay 834000, China
1 shared publication - Xueping Dai
School of Petroleum, China University of Petroleum (Beijing) at Karamay, Karamay 834000, China
1 shared publication
Latest Publications
- Open Access
- 29 April 2026
- Published by MDPI AG in Fractal and Fractional
- Vol. 10 (5) , 301
Characterization Method for the Conductive Response of Shale Based on Multi-Dimensional Fractal Theory
Resistivity is a key parameter in shale reservoir characterization. Diverse micro-pore types and complex conduction mechanisms in shale result in poor accuracy when applying existed conductivity models. Establishing a high-precision conductivity response model requires comprehensive consideration of the pore structure and clay-bound water conduction. The primary novelty of this work lies in replacing macroscopic empirical fitting parameters with a mechanistic, multi-dimensional fractal framework. We develop a novel conductivity response characterization model that explicitly couples multi-dimensional fractal pore structure theory with clay-bound water conduction. Experimental data verification demonstrates the new model’s superior characterization accuracy. Results indicate three distinct zones in the shale conductivity-pore water conductivity relationship: a nonlinear zone, a transition zone, and a linear zone. A higher cation exchange rate on clay surfaces leads to an increase in the nonlinear characteristics of the conductivity for both the shale and the pore water in low-salinity regions. An increase in the values of the conduction path fractal dimension, pore morphology fractal dimension, and pore fractal dimension all contribute to reduced shale conductivity. While sharing clay-induced conductivity terms with conventional dual-water and shale volume models, the new model offers advantages in operational simplicity and parameter accessibility. This research provides a physically rigorous and highly accessible approach for conductivity-based reservoir parameter calculation, offering new technical perspectives for complex shale oil/gas evaluation.
- 29 April 2026
- Published by MDPI AG in Fractal and Fractional
- Vol. 10 (5) , 301
Open AccessCharacterization Method for the Conductive Response of Shale Based on Multi-Dimensional Fractal Theory
Resistivity is a key parameter in shale reservoir characterization. Diverse micro-pore types and complex conduction mechanisms in shale result in poor accuracy when applying existed conductivity models. Establishing a high-precision conductivity response model requires comprehensive consideration of the pore structure and clay-bound water conduction. The primary novelty of this work lies in replacing macroscopic empirical fitting parameters with a mechanistic, multi-dimensional fractal framework. We develop a novel conductivity response characterization model that explicitly couples multi-dimensional fractal pore structure theory with clay-bound water conduction. Experimental data verification demonstrates the new model’s superior characterization accuracy. Results indicate three distinct zones in the shale conductivity-pore water conductivity relationship: a nonlinear zone, a transition zone, and a linear zone. A higher cation exchange rate on clay surfaces leads to an increase in the nonlinear characteristics of the conductivity for both the shale and the pore water in low-salinity regions. An increase in the values of the conduction path fractal dimension, pore morphology fractal dimension, and pore fractal dimension all contribute to reduced shale conductivity. While sharing clay-induced conductivity terms with conventional dual-water and shale volume models, the new model offers advantages in operational simplicity and parameter accessibility. This research provides a physically rigorous and highly accessible approach for conductivity-based reservoir parameter calculation, offering new technical perspectives for complex shale oil/gas evaluation.