知识图谱在油气勘探开发中的应用现状与发展趋势

Application status and development trend of knowledge graph in petroleum exploration and development

在油气能源产业中,知识图谱对油气资源的高效勘探开发有利于推动石油天然气工业的高质量发展。知识图谱作为一种基于人工智能和知识表示的新兴技术,逐渐成为油气勘探开发领域的研究热点和重点。为此,按照物探、钻完井、测井和油藏工程4大领域系统总结了知识图谱在石油勘探开发中的应用现状,在此基础上,结合大语言模型,剖析了知识图谱在石油勘探开发中所面临的挑战,并展望其未来发展方向。研究结果表明:(1)在油气勘探开发领域,知识图谱结合深度学习模型和专家经验,广泛应用于地质数据管理、信息解释、异常检测与分析、智能决策支持、故障诊断、测井数据综合分析、测井资料解释、测井曲线自动匹配、油藏描述、油藏数值模拟、油藏管理及设备故障维护,实现了数据质量提升、资料利用率提高和油藏动态实时监控等功能,有效提高了勘探开发效率;(2)知识图谱在油气勘探开发中面临数据多源异构、专业知识获取与表示、知识更新和维护、算力资源需求、跨学科协作与应用等挑战,需要在技术、标准、协作机制等方面进行持续探索和创新,以充分发挥知识图谱在石油勘探开发中的潜力。结论认为:(1)知识图谱技术具有广阔的应用前景,可开展油气勘探开发中的知识搜索、知识推荐、知识共享、智能问答以及知识推理、知识计算、知识图谱与大语言模型融合;(2)聚焦油气勘探开发大模型、基于机理模型和智能模型结合的仿真模型、多模态技术探索等方面的技术攻关,将推动行业向更加智能化、智慧化、高效化和精准化的方向发展。

In the energy sector,the efficient exploration and development of petroleum resources based on the knowledge graph(KG)is favorable for promoting the high-quality development of petroleum industry.KG,as an emerging technology based on artificial intelligence and knowledge representation,has become the research hotspot and focus in petroleum exploration and development.In this paper,such current applications of KG are summarized systematically in four major domains,i.e.,geophysical exploration,drilling and completion,well logging,and reservoir engineering.Then,combined with Large Language Models(LLMs),the challenges that KG encounters in the petroleum exploration and development are dissected,and the future directions are predicted.And the following research results are obtained.First,in the field of petroleum exploration and development,KG,combined with deep learning model and expert experience,is widely used in geological data management,information interpretation,anomaly detection and analysis,intelligent decision making support,fault diagnosis,comprehensive analysis of logging data,interpretation of logging data,automatic matching of logging curves,reservoir description,numerical reservoir simulation,reservoir management,and equipment fault maintenance,and achieves the functions such as data quality improvement,data utilization rate improvement,and real-time reservoir performance monitoring,effectively improving the efficiency of exploration and development.Second,when KG is applied in petroleum exploration and development,it face challenges such as multi-source heterogeneous data,acquisition and representation of professional knowledge,knowledge updating and maintenance,demand for computing resources,and interdisciplinary collaboration and application,so it needs continuous research and innovation in terms of technology,standard and collaboration mechanism to fully leverage its potential in petroleum exploration and development.In conclusion,the KG technology with promising prospects is applied to knowledge search,recommendation,sharing,intelligent question-answering,reasoning,and computation,as well as the integration of KG with LLMs in the context of petroleum exploration and development,and the technological research keeps on its focus on large-scale models for petroleum exploration and development,simulation models based on mechanism models and intelligent models,and multimodal technology,etc.,which will propel the industry to be more intelligent,efficient and precise.