The application of artificial intelligence (AI) has become inevitable in the petroleum industry. In drilling and completion engineering, AI is regarded as a transformative technology that can lower costs and significantly improve drilling efficiency (DE). In recent years, numerous studies have focused on intelligent algorithms and their application. Advanced technologies, such as digital twins and physics-guided neural networks, are expected to play roles in drilling and completion engineering. However, many challenges remain to be addressed, such as the automatic processing of multi-source and multi-scale data. Additionally, in intelligent drilling and completion, methods for the fusion of data-driven and physics-based models, few-sample learning, uncertainty modeling, and the interpretability and transferability of intelligent algorithms are research frontiers. Based on intelligent application scenarios, this study comprehensively reviews the research status of intelligent drilling and completion and discusses key research areas in the future. This study aims to enhance the berthing of AI techniques in drilling and completion engineering.

人工智能（AI）的应用在石油行业已成为必然。在钻完井工程中，人工智能被视为一种可以降低成本并显着提高钻井效率（DE）的变革性技术。近年来，大量研究集中在智能算法及其应用上。数字孪生和物理引导神经网络等先进技术有望在钻完井工程中发挥作用。然而，许多挑战仍有待解决，例如多源和多尺度数据的自动处理。此外，在智能钻完井、数据驱动和基于物理模型的融合方法、少样本学习、不确定性建模、智能算法的可解释性和可移植性是研究前沿。基于智能化应用场景，本研究全面回顾了智能钻完井的研究现状，并探讨了未来的重点研究领域。本研究旨在加强人工智能技术在钻完井工程中的靠泊。