The emergence of large language models（LLM） with characteristics of general artificial intelligence has ushered in a milestone technological revolution across industries，offering new opportunities for the intelligent transformation of petroleum engineering. This paper explores the application prospect，challenges，and development recommendations for LLM，represented by DeepSeek，in petroleum engineering. First，the fundamental concepts and technical features of LLM are introduced. Subsequently，potential application scenarios in petroleum engineering are examined，including user interaction and Q&A systems，data governance and information integration，data analysis and decision support，information parsing and intelligent assistance，and environmental monitoring and safety management. Concurrently，limitations and challenges in applying LLM to petroleum engineering are identified，such as insufficient knowledge updating capabilities，difficulties in comprehending domain-specific expertise，limited innovation in scientific research，and high training costs. Finally，recommendations and future directions for leveraging LLM in petroleum engineering are proposed，including developing specialized LLMs tailored for petroleum engineering，constructing petroleum-domain databases and information extraction frameworks，integrating internet-enabled search and real-time updating functionalities，and advancing image processing and video generation technologies. This study systematically outlines an implementation framework for LLM in petroleum engineering，providing theoretical guidance and practical references for the industry’s intelligent evolution.