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<p>The dolomite reservoirs in the Sichuan Basin exhibit complex geological characteristics, including thin bedding, rapid lateral variations, coexistence of high and low impedance reservoirs, and widespread low porosity and permeability, posing significant challenges to reservoir characterization, sweet spot prediction, and optimal well placement. Additionally, spatial mismatch between geological and engineering sweet spots further complicates effective reservoir development. This study presents an integrated three-dimensional geomechanical modeling and multi-criteria sweet spot evaluation method tailored specifically for thin-bedded carbonate reservoirs. In geological sweet spot evaluation, a lithology-based predictive model is introduced, effectively addressing the limitations of traditional seismic inversion methods, particularly low seismic resolution and poor differentiation of carbonate lithologies. For engineering sweet spot identification, natural fracture intensity is quantitatively incorporated into the evaluation framework, along with brittleness, fracture toughness, horizontal stress differences, and minimum horizontal stress. Field application in the Maokou Formation reservoirs of the Longnüsi area demonstrates that the proposed model accurately identifies high-quality reservoirs primarily concentrated in Member Maokou-2, consistent with actual drilling outcomes. Quantitative validation shows a strong positive correlation (R<sup>2</sup> = 0.856) between predicted sweet spot indices and observed gas production, confirming the reliability of the approach. Compared with other recent 3D geomechanical modeling studies, our method provides a more comprehensive integration of geological and engineering parameters, enhancing both spatial resolution and predictive robustness. Limitations include dependency on seismic resolution, uncertainties in fracture network interpretation, and computational requirements for large-scale modeling. Nevertheless, the workflow is scalable to other carbonate reservoirs with similar geological–mechanical conditions, offering a robust technical foundation for optimized exploration and efficient development of complex, thin-bedded carbonate reservoirs.</p>

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3D Geomechanical Modeling for Sweet Spot Identification in Thin-Layer Carbonate Reservoirs

  • 期刊论文

  • 发表日期：

    2025年9月24日

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  • Jian Yang,
  • Zhouyang Wang,
  • Miao Yang,
  • Yuanyu Yang,
  • Xucheng Li,
  • Le Luo,
  • Yan Fu,
  • Man Huang,
  • Zhi Zhong,
  • Dongchao Su,
  • Zikun Li,
  • Fulong Ning

摘要

The dolomite reservoirs in the Sichuan Basin exhibit complex geological characteristics, including thin bedding, rapid lateral variations, coexistence of high and low impedance reservoirs, and widespread low porosity and permeability, posing significant challenges to reservoir characterization, sweet spot prediction, and optimal well placement. Additionally, spatial mismatch between geological and engineering sweet spots further complicates effective reservoir development. This study presents an integrated three-dimensional geomechanical modeling and multi-criteria sweet spot evaluation method tailored specifically for thin-bedded carbonate reservoirs. In geological sweet spot evaluation, a lithology-based predictive model is introduced, effectively addressing the limitations of traditional seismic inversion methods, particularly low seismic resolution and poor differentiation of carbonate lithologies. For engineering sweet spot identification, natural fracture intensity is quantitatively incorporated into the evaluation framework, along with brittleness, fracture toughness, horizontal stress differences, and minimum horizontal stress. Field application in the Maokou Formation reservoirs of the Longnüsi area demonstrates that the proposed model accurately identifies high-quality reservoirs primarily concentrated in Member Maokou-2, consistent with actual drilling outcomes. Quantitative validation shows a strong positive correlation (R2 = 0.856) between predicted sweet spot indices and observed gas production, confirming the reliability of the approach. Compared with other recent 3D geomechanical modeling studies, our method provides a more comprehensive integration of geological and engineering parameters, enhancing both spatial resolution and predictive robustness. Limitations include dependency on seismic resolution, uncertainties in fracture network interpretation, and computational requirements for large-scale modeling. Nevertheless, the workflow is scalable to other carbonate reservoirs with similar geological–mechanical conditions, offering a robust technical foundation for optimized exploration and efficient development of complex, thin-bedded carbonate reservoirs.