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<p>This study establishes a multi-physics-coupled dynamic analysis model to investigate the risk evolution of oil and gas intrusion in high-temperature high-pressure (HTHP) drilling operations. By integrating genetic neural networks for seismic attribute screening with acoustic data and dynamic Bayesian networks (DBN), the evolutionary patterns of leakage, collapse, and overflow risks are systematically analyzed. The research elucidates the driving mechanisms of oil and gas intrusion under HTHP conditions, including pressure gradients, capillary effects, stress redistribution, and non-Darcy flow, and proposes a three-stage dynamic process for intrusion channel formation (initial, dynamic, and sudden risk phases). Safety barrier failure analysis identifies critical failure modes of drilling fluid, blowout preventers (BOPs), and casing systems under extreme conditions: rheological degradation of drilling fluid, material performance attenuation of casing, and BOP seal failure. Quantitative assessment via DBN models evaluates the coupling effects of equipment failures, abnormal formation pressure, and human errors, constructing a multidimensional risk propagation framework encompassing equipment, environment, personnel, and management factors. A hybrid evaluation method combining data-driven analysis and numerical simulation is proposed, offering theoretical and technical foundations for proactive risk management in deep-sea drilling.</p>

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Construction of Complex Well Control Scenarios and Analysis of Risk Evolution Law

  • 期刊论文

  • 发表日期：

    2025年11月1日

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  • Qiang Cui,
  • Xiaoshan Wang,
  • Kang Qiu,
  • Haoyu Pu,
  • Xinyue Zhang,
  • Juyan Zhang

摘要

This study establishes a multi-physics-coupled dynamic analysis model to investigate the risk evolution of oil and gas intrusion in high-temperature high-pressure (HTHP) drilling operations. By integrating genetic neural networks for seismic attribute screening with acoustic data and dynamic Bayesian networks (DBN), the evolutionary patterns of leakage, collapse, and overflow risks are systematically analyzed. The research elucidates the driving mechanisms of oil and gas intrusion under HTHP conditions, including pressure gradients, capillary effects, stress redistribution, and non-Darcy flow, and proposes a three-stage dynamic process for intrusion channel formation (initial, dynamic, and sudden risk phases). Safety barrier failure analysis identifies critical failure modes of drilling fluid, blowout preventers (BOPs), and casing systems under extreme conditions: rheological degradation of drilling fluid, material performance attenuation of casing, and BOP seal failure. Quantitative assessment via DBN models evaluates the coupling effects of equipment failures, abnormal formation pressure, and human errors, constructing a multidimensional risk propagation framework encompassing equipment, environment, personnel, and management factors. A hybrid evaluation method combining data-driven analysis and numerical simulation is proposed, offering theoretical and technical foundations for proactive risk management in deep-sea drilling.