基于数字孪生技术的钻井复杂风险智能预警系统架构

Architecture of Intelligent Early Warning System for Complex Drilling Risks Based on Digital Twin Technology

为降低深部地层不确定地质条件诱发的钻井井下复杂风险,采用数字孪生技术,构建了基于物理模型与数据驱动模型融合的钻井复杂风险数字孪生智能预警体系。为满足随钻预警、降低风险等实际需求,提出了基于微服务的数据集成、孪生体智能感知、多模态融合预警、孪生体智能诊断等4项数字孪生预警系统支撑技术,建立了钻井数字孪生预警系统的整体架构,并详述了其功能及模型设计,涉及物理设备层、虚拟实体层、孪生体数据层、孪生体算法模型层及孪生体预警服务层5层交互系统,设计了钻前预演规避风险、钻中实时预警、钻后分析区块风险等3种区块钻井优化设计的应用场景,实现了对多源异构数据的数字化集成,传统物理模型与智能模型的多重融合,以及溢流、井漏、卡钻的预警与类型识别等功能,从而达到降低深部钻井作业风险、优快钻井的目的。研究结果表明,基于“模型+数据”的数字孪生预警架构具有提前识别钻井过程中的风险和快速诊断风险类型的潜力,为智能钻井风险预警提供了新的技术途径。

To reduce the complex drilling risks induced by uncertain geological conditions in deep formations,the digital twin technology has been adopted to construct a digital twin intelligent risk early warning system for complex drilling risks based on the fusion of physical models and data-driven models.In order to meet the actual requirements of early warning while drilling and risk reduction,four supporting technologies of digital twin early warning system were proposed,including microservice-based data integration,intelligent perception of digital twins,multimodal fusion early warning,and intelligent diagnosis of digital twins.The overall architecture of the digital twin early warning system for drilling has been established,and its functions and model design were described in detail.The system involved a fivelayer interaction system,including physical device layer,virtual entity layer,digital twin data layer,digital twin algorithm model layer,and digital twin early warning service layer.Three application scenarios have been designed,including pre-drilling risk avoidance rehearsal,real-time warning during drilling,and post-drilling analysis of block risk situations to optimize block drilling design.This system has achieved several functions,such as digital integration of multi-source heterogeneous data,multiple fusion of traditional physical models with intelligent models,warning and type identification of overflow,lost circulation,and pipe sticking,etc.Therefore,the risks associated with deep drilling operations have been reduced and drilling efficiency has been optimized.The study results indicate that the digital twin warning architecture based on“model+data”has the potential to identify drilling risks and diagnose risk types in advance during drilling,providing new technology approaches for intelligent drilling risk early warning.