Spatio-temporal fractal structures in sedimentary sequences and their geological significance

doi:10.13745/j.esf.sf.2025.8.67

Abstract

Abstract:

The formation of sedimentary sequences is controlled by tectonic activity, sea (lake)-level change, and climate evolution, resulting in complex multiscale spatiotemporal structures. While traditional methods struggle to reveal their intrinsic patterns, fractal theory offers a novel approach. Using the Shahejie Formation in the Jiyang Depression as a case study, this research systematically analyzes the spatiotemporal fractal structures of sedimentary sequences and their geological implications. First, the Hurst index quantifies temporal fractal characteristics to interpret sedimentary environment evolution. Second, power spectral density analysis reveals self-organized criticality (SOC) of the sedimentary system, and a filter-based technique for extracting long-range spatiotemporal correlations is proposed. Finally, fractal dimensions of pore structures are characterized to quantitatively evaluate their impact on reservoir permeability. Results demonstrate that: (1) The Hurst index quantifies long-term sedimentary trends; (2) SOC optimizes reservoir parameter analysis; (3) Fractal theory critically supports pore-throat structure evaluation. This study advances understanding of sedimentary complexity and provides new theoretical/methodological foundations for hydrocarbon exploration and reservoir assessment.

Key words: fractal theory, spatio-temporal fractal structure, Hurst index, power spectrum analysis, pore throat structure evaluation

CLC Number:

RUAN Zhuang, WANG Yueyun, CHANG Qiuhong, YU Bingsong. Spatio-temporal fractal structures in sedimentary sequences and their geological significance[J]. Earth Science Frontiers, 2025, 32(6): 350-366.

Figures/Tables 12

Fig.1 Calculation process of Hurst index. Modified after [61].

Fig.2 Fourth cycle correlation between well L69, FY1 and NY1. Modified after [72-75].

Fig.3 Relationship diagram among Hurst index, FST and D

Fig.4 Summary of HI, D, FST, lithological, and subfacies content for fourth cycles

Fig.5 Power spectrum characteristics of reservoir parameters of 3 core wells in Dongying Depression

Fig.6 Definition of curvature

Fig.7 Function fitting and curvature of reservoir parameter power spectrum curve of 3 core wells in Dongying Depression

Fig.8 Filter map of reservoir parameters of 3 core wells in Dongying Depression

Fig.9 Correlation diagram between reservoir parameters and S1 of 3 core wells in Dongying Depression

Fig.10 The pore throat sizes and their distribution of sandstone samples in Dongying Sag

Fig.11 Relationship between E(x) and Df, τ and DT in Dongying sag

Fig.12 Relationship between logK and Df, τ and DT in Dongying sag

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