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<p>Ultra-deep carbonate reservoirs in the Permian Qixia Formation of the Sichuan Basin, particularly those exceeding 7000&#xa0;m in depth, have emerged as a significant focus for exploration and development. However, production capacities between adjacent wells can vary by up to two orders of magnitude due to the multi-scale heterogeneity of pore connectivity, which poses challenges for accurately predicting well performance. This study utilizes thin-section analysis, high-pressure mercury injection (HPMI), scanning electron microscopy (SEM), and other techniques to investigate pore connectivity in ultra-deep reservoirs. It also explores methods for evaluating the connectivity of multi-scale pore networks in the Qixia Formation. The analysis reveals distinct permeability contribution patterns and connectivity characteristics across different reservoir types. Results indicate that the carbonate reservoirs in the Qixia Formation are predominantly composed of dolomite, with intercrystalline pores, dissolution pores, and fractures constituting the primary pore types. The pore-throat size distribution exhibits significant heterogeneity, as evidenced by a multi-peak distribution curve. Approximately 25% of the reservoirs contain well-connected pores, and a threshold radius (r<sub>25</sub>) is identified as a key parameter for assessing connectivity. Overall, pore connectivity within the reservoirs is limited, with fractures playing a critical role in linking isolated pore spaces. This study introduces the parameter SH<sub>gf</sub>, which quantitatively evaluates the connectivity of multi-scale pore networks and distinguishes the abundance of fractures within the reservoir using a boundary value of 7%. By analyzing fluid seepage patterns, a permeability contribution model for the four identified reservoir types is established, providing a robust framework for assessing reservoir connectivity. These findings offer valuable insights for predicting production capacities and optimizing development strategies in ultra-deep carbonate reservoirs.</p>

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Pore connectivity evaluation and seepage characteristic of ultra deep carbonate reservoirs of permian Qixia formation in NW Sichuan basin

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月22日

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  • Hao Lu,
  • Zike Ma,
  • Hu Li,
  • Penglei Yan,
  • Xian Liu,
  • Jiale Liu,
  • Cheng Ma,
  • Bo Kang,
  • Boning Zhang,
  • Yulong Zhao,
  • Liehui Zhang

摘要

Ultra-deep carbonate reservoirs in the Permian Qixia Formation of the Sichuan Basin, particularly those exceeding 7000 m in depth, have emerged as a significant focus for exploration and development. However, production capacities between adjacent wells can vary by up to two orders of magnitude due to the multi-scale heterogeneity of pore connectivity, which poses challenges for accurately predicting well performance. This study utilizes thin-section analysis, high-pressure mercury injection (HPMI), scanning electron microscopy (SEM), and other techniques to investigate pore connectivity in ultra-deep reservoirs. It also explores methods for evaluating the connectivity of multi-scale pore networks in the Qixia Formation. The analysis reveals distinct permeability contribution patterns and connectivity characteristics across different reservoir types. Results indicate that the carbonate reservoirs in the Qixia Formation are predominantly composed of dolomite, with intercrystalline pores, dissolution pores, and fractures constituting the primary pore types. The pore-throat size distribution exhibits significant heterogeneity, as evidenced by a multi-peak distribution curve. Approximately 25% of the reservoirs contain well-connected pores, and a threshold radius (r25) is identified as a key parameter for assessing connectivity. Overall, pore connectivity within the reservoirs is limited, with fractures playing a critical role in linking isolated pore spaces. This study introduces the parameter SHgf, which quantitatively evaluates the connectivity of multi-scale pore networks and distinguishes the abundance of fractures within the reservoir using a boundary value of 7%. By analyzing fluid seepage patterns, a permeability contribution model for the four identified reservoir types is established, providing a robust framework for assessing reservoir connectivity. These findings offer valuable insights for predicting production capacities and optimizing development strategies in ultra-deep carbonate reservoirs.