油气井工程多源多模态数据融合技术与展望

Multi-source and multi-modal data fusion technology and its prospect in oil and gas well engineering

随着油气田数字化、智能化建设的不断推进,数据量迅速增长,传统的数据融合方法已无法满足油气井工程领域对多来源、多模态数据的利用需求。为此,从油气井工程业务的角度出发,详细阐述了多来源、多模态及多领域数据的特征,并对不同类型的数据融合应用场景和优缺点进行了系统分析,重点讨论了数据融合的关键技术和当前面临的挑战,最后结合空间尺度、时间尺度、边界信息和模糊信息的融合需求,提出了面临的技术挑战和解决思路。研究结果表明:(1)油气井工程领域数据具有多来源、多模态和多领域的特征,这使得数据分析和应用极为复杂和丰富;(2)从整体融合的角度出发,结合最终目标,逐步划分数据融合过程,可提高融合过程的可执行性;(3)在油气井工程行业应用数据时,应始终注重实际应用需求,通过强化数据集成、构建融合模型、开发高性能融合架构和自适应融合方法,进而推动数据融合技术的发展,以应对日益复杂的数据环境和业务需求挑战。结论认为,数据融合作为一个跨学科、跨领域的交叉学科研究问题,亟需在深度和广度上进行创新,以提升油气井工程领域数据的有效利用率,对于提升油气井工程数字化和智能化具有重要的指导作用和意义。

With the advancement of digital and intelligent construction of oil and gas fields,the volume of data increases rapidly,which makes the traditional data fusion methods fail to meet the utilization demand of multi-source and multi-modal data in the domain of oil and gas well engineering.This paper illustrates the characteristics of multi-source,multi-modal,and multi-domain data from the perspective of oil and gas well engineering.Then,the application scenarios,advantages,and disadvantages of different types of data fusion are analyzed systematically,and the key technologies and current challenges to data fusion are mainly discussed.Finally,the technical challenges and the corresponding solving ideas are described based on the fusion needs of spatial scale,temporal scale,boundary information and fuzzy information.And the following research results are obtained.First,the data in the domain of oil and gas well engineering have the characteristics of multiple sources,multiple modals and multiple domains,which make data analysis extremely complicated and rich.Second,the data fusion process is divided step by step from the perspective of entire fusion,combined with the ultimate objective,which can improve the performability of fusion process.Third,during the data application in the oil and gas well engineering industry,attention shall be always paid to the needs of actual application.It is necessary to promote the development of data fusion technologies by enhancing data integration,constructing fusion models and developing high-performance fusion architectures and adaptive fusion methods,so as to cope with the increasingly complex data environments and business challenges.In conclusion,as an interdisciplinary and cross-domain research issue,data fusion necessitates innovative approaches in both depth and breadth to enhance the effective data utilization in the domain of oil and gas well engineering,which is of great guidance and significance for facilitating the digitization and intelligence of oil and gas well engineering.