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<p>Core classification plays a critical role in reservoir evaluation as well as in oil and gas exploration, coalbed methane development, and groundwater resource assessment. In this study, multifractal analysis was applied to limestone and coal samples from a coal mine in North China, based on capillary pressure curves obtained through high-pressure mercury intrusion (HPMI) experiments. The results demonstrate that limestone samples can be effectively classified using multifractal parameters such as α<sub>0</sub>-α<sub>min</sub> and f(α<sub>0</sub>)-f(α<sub>min</sub>), which closely correspond to variations in permeability and pore structure. For coal samples, parameters including α<sub>0</sub>, D<sub>0</sub>, Δτ, α<sub>0</sub>-α<sub>min</sub>, and f(α<sub>0</sub>)-f(α<sub>min</sub>) reflect differences in pore complexity and connectivity associated with coal rank, enabling distinction between low-rank and medium- to high-rank coals. This multifractal-based classification method quantitatively captures the heterogeneity and hierarchical structure of pore systems, offering both scientific insight and practical applicability. These findings provide a robust framework for fine-scale reservoir characterization and a new approach to core classification in unconventional energy systems.</p>

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Multifractal classification of rock cores based on mercury intrusion experiments

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月7日

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  • Jinsui Wu,
  • Ying Li,
  • Ping Ji,
  • Dezhi Hu,
  • Shangxian Yin,
  • Yulu Yan

摘要

Core classification plays a critical role in reservoir evaluation as well as in oil and gas exploration, coalbed methane development, and groundwater resource assessment. In this study, multifractal analysis was applied to limestone and coal samples from a coal mine in North China, based on capillary pressure curves obtained through high-pressure mercury intrusion (HPMI) experiments. The results demonstrate that limestone samples can be effectively classified using multifractal parameters such as α0-αmin and f(α0)-f(αmin), which closely correspond to variations in permeability and pore structure. For coal samples, parameters including α0, D0, Δτ, α0-αmin, and f(α0)-f(αmin) reflect differences in pore complexity and connectivity associated with coal rank, enabling distinction between low-rank and medium- to high-rank coals. This multifractal-based classification method quantitatively captures the heterogeneity and hierarchical structure of pore systems, offering both scientific insight and practical applicability. These findings provide a robust framework for fine-scale reservoir characterization and a new approach to core classification in unconventional energy systems.