Xinyi Zhang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Xinyi Zhang has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Dingxue Zhang
School of Petroleum Engineering, Yangtze University, Wuhan, China
1 shared publication - Liang Zhao
Research Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, China
1 shared publication - Lingfeng Zhao
School of Petroleum Engineering, Yangtze University, Wuhan 430100, China
1 shared publication
Latest Publications
- Open Access
- 7 November 2025
- Published by MDPI AG in Fractal and Fractional
- Vol. 9 (11) , 719
Deciphering Shale Gas Production Dynamics: A Fractal Theory Approach
Shale gas production dynamics display strong heterogeneity and nonlinearity, posing challenges to conventional analytical methods. This study applies fractal theory to analyze long-term production data from 178 global shale gas fields by calculating Hurst exponent (H) and fractal dimension (D). Results show 60.7% of fields are suitable for fractal analysis, with H values of 0.64–0.92 and D values of 1.0–1.9, indicating significant long-term memory and structural complexity. Cluster analysis reveals two distinct production patterns: stable trend (13.0%) and fluctuating trend (87.0%). Key innovations include: (1) extending fractal theory from static reservoir characterization to dynamic production analysis; (2) establishing a fractal-based production classification system; and (3) defining applicability conditions for fractal analysis in shale gas evaluation. This study demonstrates fractal theory’s effectiveness as a quantitative tool for production dynamics analysis, EUR estimation, and development strategy optimization.
- 7 November 2025
- Published by MDPI AG in Fractal and Fractional
- Vol. 9 (11) , 719
Open AccessDeciphering Shale Gas Production Dynamics: A Fractal Theory Approach
Shale gas production dynamics display strong heterogeneity and nonlinearity, posing challenges to conventional analytical methods. This study applies fractal theory to analyze long-term production data from 178 global shale gas fields by calculating Hurst exponent (H) and fractal dimension (D). Results show 60.7% of fields are suitable for fractal analysis, with H values of 0.64–0.92 and D values of 1.0–1.9, indicating significant long-term memory and structural complexity. Cluster analysis reveals two distinct production patterns: stable trend (13.0%) and fluctuating trend (87.0%). Key innovations include: (1) extending fractal theory from static reservoir characterization to dynamic production analysis; (2) establishing a fractal-based production classification system; and (3) defining applicability conditions for fractal analysis in shale gas evaluation. This study demonstrates fractal theory’s effectiveness as a quantitative tool for production dynamics analysis, EUR estimation, and development strategy optimization.