State Prediction Method for Deepwater Drilling Riser System Based on Limited Monitoring Data

Zhao Ronggen; Jia Guole; Jin Xueyi; Liu Xiuquan

doi:10.12473/CPM.202506065

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State Prediction Method for Deepwater Drilling Riser System Based on Limited Monitoring Data

OFFSHORE PETROLEUM EQUIPMENT | 更新时间：2026-11-04

- State Prediction Method for Deepwater Drilling Riser System Based on Limited Monitoring Data
- China Petroleum Machinery Vol. 54, Issue 10, Pages: 71-78(2026)
- 作者机构：
  
  1.中国石油大学（华东）机电工程学院
  2.中海油田服务股份有限公司
- 作者简介：
- 基金信息：
- DOI：10.12473/CPM.202506065
  CLC： TE58
- Received：23 June 2025，
  
  Revised：2026-07-06，
  
  Accepted：14 November 2025，
  
  Published：25 October 2026
- 稿件说明：
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赵荣根，贾国乐，金学义，等.基于有限监测数据的深水钻井隔水管系统状态预测方法［J］.石油机械，2026，54（10）：71-78.

Zhao Ronggen，Jia Guole，Jin Xueyi，et al.State Prediction method for deepwater drilling riser system based on limited monitoring data［J］.China Petroleum Machinery，2026，54（10）：71-78.
赵荣根，贾国乐，金学义，等.基于有限监测数据的深水钻井隔水管系统状态预测方法［J］.石油机械，2026，54（10）：71-78. DOI： 10.12473/CPM.202506065.

Zhao Ronggen，Jia Guole，Jin Xueyi，et al.State Prediction method for deepwater drilling riser system based on limited monitoring data［J］.China Petroleum Machinery，2026，54（10）：71-78. DOI： 10.12473/CPM.202506065.

摘要

深水钻井隔水管系统是海洋油气钻探的关键设备，其动力响应特性直接关系到整个钻井作业的安全性。然而，由于深海环境复杂多变且监测数据有限，在有限数据下实现系统全状态动态响应的实时准确预测面临重大挑战。针对这一问题，提出了一种有限监测数据下深水钻井隔水管系统动力响应实时状态预测方法。该方法使用上部挠性接头转角及平台升沉、横荡和垂荡监测数据预测深水钻井隔水管系统动力响应状态。根据设计海况进行深水钻井隔水管全耦合系统动力响应分析，以得到的时序数据为基础，利用蚁群算法优化门控循环神经网络（GRU）建立系统状态预测模型，并对预测模型进行验证。研究结果表明：该隔水管系统状态响应参数预测模型的准确度较高，其决定系数大于0.97，显示出较高的预测精度与稳定性，可使用GRU进行深水钻井隔水管系统动力响应状态预测。研究结果可为深水钻井隔水管系统动力响应状态实时预测提供理论依据及技术支撑。

Abstract

Deepwater drilling riser system is a critical component for offshore oil and gas drilling， and its dynamic response characteristics are directly related to the overall safety of drilling operations. However， due to the complex and variable deep-sea environment and limited monitoring data， real-time and accurate prediction of the system's full-state dynamic responses is highly chal

lenging. This paper proposes a real-time state prediction method for the dynamic response of deepwater drilling riser system based on limited monitoring data. This method uses the monitoring data of the upper flexible joint rotation angle and the platform heave， surge， and sway motions， to predict the system's dynamic response state. The dynamic response analysis of the fully-coupled deepwater drilling riser system was conducted depending on designed sea conditions. Based on the time-series data obtained from the analysis， the gated recurrent unit （GRU） neural network optimized by the ant colony algorithm was employed to establish the system state prediction model. Finally， the prediction model was validated. The results show that the proposed model achieves accurate prediction， with the coefficient of determination （

） exceeding 0.97， indicating high accuracy and stability， and that GRU can be used to predict the dynamic response states of deepwater drilling riser systems. The study provides a theoretical basis and technical support for real-time prediction of deepwater drilling riser system's dynamic response state.

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