JOURNAL ARTICLE

Fractal characteristics of micropore structure of Taiyuan Formation bauxite reservoir in Longdong area of Ordos Basin.

  • Published In: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.), 2025, v. 25, n. 4. P. 3311 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Dong, Yue; Yang, Xiaochen; Hu, Chenguanng; Zhou, Jiang; Li, Yongjin; Qin, Qin; Yin, Zhaoyang; Li, Haoyuan; Zhu, Yushuang 3 of 3

Abstract

This article focuses on the geological and reservoir characteristics of the Taiyuan Formation bauxite gas reservoirs in the Longdong area of the Ordos Basin, China. It identifies the bauxite reservoirs as sedimentary formations with distinct logging features—high natural gamma ray readings (around 500 API) and low acoustic wave time differences—and classifies them based on diaspore mineral content into bauxite, argillaceous bauxite, and aluminous mudstone. The reservoir pores mainly consist of dissolution pores within particles, intergranular pores, and microcracks, with an average porosity of 8.49% and low permeability averaging 0.261 × 10⁻³ μm². Using high-pressure mercury injection and low-temperature nitrogen adsorption experiments, fractal dimensions were calculated to evaluate pore structure, leading to a classification system where Type I reservoirs (D1 fractal dimension 2.2–2.6) represent high-quality targets for exploration. The study highlights the significance of micro ancient landforms, especially buried pits, in influencing bauxite thickness and reservoir quality.

Additional Information

  • Source:Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2025/07, Vol. 25, Issue 4, p3311
  • Document Type:Article
  • Subject Area:Geology
  • Publication Date:2025
  • ISSN:1472-7978
  • DOI:10.1177/14727978251320197
  • Accession Number:185657848
  • Copyright Statement:Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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