Abstract: In this era of Internet and Big Data，the application of machine learning，which is the core of artificial intelligence，in drilling engineering represents a general future development orientation. Drilling engineering is an essential part of hydrocarbon exploration and development technology. Machine learning-based drilling parameter optimization and accident prediction and warning are vital for economy，safety，efficiency，and environmental-friendliness. Given that it is hard to effectively guide the drilling operation for deep and ultra-deep wells using the previous experience and data，this research summarizes the present algorithms used in machine learning first，and gives a preliminary analysis for the benefits of machine learning in drilling engineering consequently. A review of global studies on applications of machine learning in drilling engineering is presented and the challenges are identified. Some suggestions are proposed，in an attempt to promote contributions of machine learning in the development of drilling engineering of China.

Key words: artificial intelligence, machine learning, drilling engineering

摘要： 在互联网大数据时代，人工智能的核心—机器学习方法应用在钻井工程中是未来发展的大方向。其中钻井工程作为油气勘探开发过程中的中坚力量，利用机器学习方法优化钻井参数、进行事故预测与预警对于指导钻井工作经济、安全、高效、环保进行具有重要意义。针对利用以往经验、数据难以有效指导深井超深井钻井工作的情况，对目前机器学习所使用的算法进行了概述，浅析了机器学习应用在钻井工程中带来的益处，结合实际钻井工程需求调研了目前国内外机器学习在钻井工程中的一些实际应用，指出了机器学习在钻井工程中应用时面临的问题所在，对指出的问题提出了几点解决方法，期望机器学习技术能为我国钻井工程的发展添砖加瓦。

关键词: 人工智能, 机器学习, 钻井工程