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<p>Conventional perforation often leads to the formation of a compacted zone around the perforation tunnel, severely impairing near-wellbore permeability and well productivity. This study focuses on Dynamic Negative Pressure Perforation (DNPP) as a solution to effectively remove this damage. We first established a mathematical model to characterize downhole pressure transients during DNPP. Subsequently, a 3D fluid-solid coupled numerical model was developed to simulate the cleanup process of the compacted zone. Through orthogonal experiments and stepwise regression analysis, we identified the key controlling factors and constructed a predictive model for cleanup efficiency. The results show that DNPP can significantly enhance the flow capacity of perforation channels by efficiently clearing the compacted debris. The maximum dynamic negative pressure, initial static negative pressure, rock cohesion, and internal friction angle are the dominant parameters determining the cleanup outcome. This work provides a mechanistic understanding and a practical predictive tool for optimizing DNPP design to improve well performance.</p>

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Investigation into the mechanism of damage removal in the compaction zone using dynamic negative pressure perforation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月6日

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  • Fuguo Li,
  • Yuchen Li,
  • Zhiqiang Zhang,
  • Feng Li,
  • Changhao Wang,
  • Yao Wang

摘要

Conventional perforation often leads to the formation of a compacted zone around the perforation tunnel, severely impairing near-wellbore permeability and well productivity. This study focuses on Dynamic Negative Pressure Perforation (DNPP) as a solution to effectively remove this damage. We first established a mathematical model to characterize downhole pressure transients during DNPP. Subsequently, a 3D fluid-solid coupled numerical model was developed to simulate the cleanup process of the compacted zone. Through orthogonal experiments and stepwise regression analysis, we identified the key controlling factors and constructed a predictive model for cleanup efficiency. The results show that DNPP can significantly enhance the flow capacity of perforation channels by efficiently clearing the compacted debris. The maximum dynamic negative pressure, initial static negative pressure, rock cohesion, and internal friction angle are the dominant parameters determining the cleanup outcome. This work provides a mechanistic understanding and a practical predictive tool for optimizing DNPP design to improve well performance.