基于边缘粒子滤波的钻井过程在线监测

Amadou Ba, N. Mechbal, M. Vergé, S. Hbaieb
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引用次数: 1

摘要

钻井过程的实时监测是提高钻井性能的重要任务。为了保证钻井效率,必须尽快发现可能发生的故障。本文研究了利用边缘粒子滤波(MPF)识别时变参数的钻井过程监测问题。其思想在于通过在过程模型中集成一个表示故障过程的部分和另一个表示安全过程的部分来增强参数变化的跟踪能力。仿真和实验数据表明,该方法的有效性得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-line drilling process monitoring by Marginalized Particle Filter
Real-time monitoring of a drilling process is an essential task in improving their performances. Faults that might occur have to be detected as soon as possible in order to preserve drilling efficiency. In this paper, drilling process monitoring by identifying time varying parameters through Marginalized Particle Filter (MPF) is treated. The idea consists in enhancing the tracking ability of parameters change by integrating into the process model a part that represents the faulty process and another when the process is safe. The efficiency of the developed approach is highlighted through simulated and experimental data obtained from tests campaign.
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