基于人工智能的钻井工程异常预警系统研究及应用

Research and Application of Anomaly Early-warning System on Well Drilling Engineering Based on Artificial Intelligence

石油勘探开发过程中,钻井工程异常预警系统已实现主动预警,但仍存在跨系统、跨平台数据间通信和共享能力不足,预警类型单一等问题。引入人工智能技术,设计了融合井场多元数据分析诊断的钻井工程异常预警系统。该系统借鉴类似情况下钻井异常处理经验,在及时、准确地完成钻井异常预警任务的同时自学习、自增长,对于保障钻井安全生产、提高钻井效益均有重要意义。

s:Anomaly early-warning system for well drilling engineering has realized with positive pre-warning in the petroleum exploration.But there are problems of insufficient capacity of the data communicating and sharing between system and platform,and the earlywarning type is single.An anomaly early-warning system for well drilling engineering with adopting artificial intelligence technology and integration of well site multivariate data analysis and diagnosis is designed.With referring the experience of abnormity handling in similar situations for well drilling,the system can self-learn and self-grow while completing the well drilling abnormity early-warning task timely and accurately.It is of great significance to ensure the safe production of well drilling and improve the well drilling profit.