A Full-Scale Pore Fractal Modeling Approach for Tight Sandstone Reservoirs Integrating HPMI and LTNA Data

Conventional high-pressure mercury injection (HPMI) alone inadequately characterizes the fractal properties of nanopores in tight sandstone reservoirs, and existing fractal models for HPMI, low-temperature nitrogen adsorption (LTNA), and nuclear magnetic resonance (NMR) lack effective integration. Based on traditional fractal theory, this study develops a unified full-scale pore fractal model that integrates HPMI and LTNA data via a defined conversion coefficient. The model was validated using tight sandstone samples from the Songliao Basin in eastern China and the Turpan–Hami Basin in western China. Results indicate that the proposed model successfully achieves accurate characterization of full-scale pore fractal behavior. Furthermore, it provides a robust fractal-based framework for calibrating NMR T2 relaxation time and constructing enhanced full-scale pore-throat distribution profiles, thereby validating its effectiveness and practical utility as defined in our objectives.

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Publication Details

Journal
Fractal and Fractional
Published
2026-01-30
DOI
https://doi.org/10.3390/fractalfract10020096
Primary Topic
Hydrocarbon exploration and reservoir analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

A Full-Scale Pore Fractal Modeling Approach for Tight Sandstone Reservoirs Integrating HPMI and LTNA Data

Jingkai Wen, Changsheng Miao, Haobo Lu, Xiyu Qu et al.
Fractal and Fractional
Hydrocarbon exploration and reservoir analysis
article

A Full-Scale Pore Fractal Modeling Approach for Tight Sandstone Reservoirs Integrating HPMI and LTNA Data

Jingkai Wen, Changsheng Miao, Haobo Lu, Xiyu Qu, Yangchen Zhang
article en

Abstract

Conventional high-pressure mercury injection (HPMI) alone inadequately characterizes the fractal properties of nanopores in tight sandstone reservoirs, and existing fractal models for HPMI, low-temperature nitrogen adsorption (LTNA), and nuclear magnetic resonance (NMR) lack effective integration. Based on traditional fractal theory, this study develops a unified full-scale pore fractal model that integrates HPMI and LTNA data via a defined conversion coefficient. The model was validated using tight sandstone samples from the Songliao Basin in eastern China and the Turpan–Hami Basin in western China. Results indicate that the proposed model successfully achieves accurate characterization of full-scale pore fractal behavior. Furthermore, it provides a robust fractal-based framework for calibrating NMR T2 relaxation time and constructing enhanced full-scale pore-throat distribution profiles, thereby validating its effectiveness and practical utility as defined in our objectives.

Fractal and FractionalVol. 10(2)
Changchun Institute of Technology (CN), China University of Petroleum, East China (CN)
China University of Petroleum, Beijing, Natural Science Foundation of Shandong Province, National Science and Technology Major Project, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 71%
Hydrocarbon exploration and reservoir analysis
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A Full-Scale Pore Fractal Modeling Approach for Tight Sandstone Reservoirs Integrating HPMI and LTNA Data — Jingkai Wen, Changsheng Miao, et al. · Fractal and Fractional (2026) | TGRS Research Map | TGRS