Applications and Prospect of DeepSeek Large Language Model in Petroleum Engineering

doi:10.12388/j.issn.1673-2677.2025.02.006

Abstract

Abstract:

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.

Key words:

DeepSeek, large language model, petroleum engineering, intelligence, prospect

摘要：

大语言模型表现出的通用人工智能特征，为各行业带来了里程碑式的技术革命，也为石油工程智能化转型提供了新的机遇。探讨以DeepSeek为代表的大语言模型在石油工程领域的应用前景、挑战和发展建议。首先，介绍了大语言模型的基本概念和技术特性，然后分析了其在石油工程中的潜在应用场景，如用户交互与问答系统、数据治理与信息整合、数据分析与决策支持、信息解析与智能辅助、环境监测与安全管理等；其次，指出了其在石油工程中存在的局限和挑战，如知识更新能力不够、难以理解专业知识、科研创新性不足和训练成本较高等；最后，提出了大语言模型在石油工程应用中的建议和展望，包括建立针对石油工程的专业化大模型、油气领域数据库与信息提取、联网搜索与实时更新功能、图像处理与视频生成技术等方面的发展方向，并系统探讨了大语言模型在石油工程中的实施框架，为行业智能化升级提供理论指导与实践参考。

关键词:

"> DeepSeek, 大语言模型, 石油工程, 智能化, 前景展望

CLC Number:

TIAN Huiyang, LIU Ruiheng, LI Dongshuang, YOU Shaohua, LIAO Qinzhuo, TIAN Shouceng.

Applications and Prospect of DeepSeek Large Language Model in Petroleum Engineering

[J]. Xinjiang Oil & Gas, 2025, 21(2): 55-.

田慧洋, 刘瑞恒, 李冬爽, 尤少华, 廖勤拙, 田守嶒.

DeepSeek大模型在石油工程中的应用前景与展望

[J]. 新疆石油天然气, 2025, 21(2): 55-.

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