Research on Key Technology of Intelligent and Safe Operation and Maintenance of High-End Drilling Equipment
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摘要: 随着深层-超深层能源资源勘探需求增加，高端油气钻探装备面临着环境严苛、工况极限、故障耦合、维保困难的挑战，现有的运维模式多依赖于人工经验和定期检查，无法实现故障早期预测与及时处理，安全问题突出. 针对高端油气钻探装备在运维过程中面临的问题与挑战，提出了一种创新的智能安全运维技术，以全过程、全要素、全生命周期运行维护为目标，以全生命周期管理和主动运维优化构建智能运维闭环流程，通过融合信息化赋能技术及运维本体技术推动油气钻探装备运维从传统运维模式向智能安全运维模式转型. 开发了具备状态监测、健康评估、故障诊断以及智能决策功能模块的智能安全运维系统，实现某海上钻井平台关键设备智能运维，为智能安全运维技术在油气领域快速应用提供思路.Abstract: As the demand for deep and ultra-deep energy resource exploration continues to rise, high-end oil and gas drilling equipment faces significant challenges, including harsh environmental conditions, extreme operating scenarios, fault coupling, and maintenance difficulties. The current operation and maintenance practices largely rely on manual experience and periodic inspections, which fail to enable early fault prediction and timely response, leading to prominent safety concerns. To address the issues and challenges encountered during the operation and maintenance of high-end oil and gas drilling equipment, this paper proposes an innovative intelligent and safe operation and maintenance technology. Aiming for comprehensive, element-wide, and full life cycle operation and maintenance, the study constructs a closed-loop intelligent operation and maintenance process based on life cycle management and proactive maintenance optimization. By integrating digital empowerment technologies with domain-specific operation and maintenance technologies, the approach promotes the transformation from traditional to intelligent and safe operation and maintenance models for oil and gas drilling equipment. An intelligent and safe operation and maintenance system for drilling equipment is developed, incorporating functional modules for condition monitoring, health assessment, fault diagnosis, and intelligent decision-making. The system is successfully applied to the intelligent operation and maintenance of drilling equipment on an offshore drilling platform, providing a valuable reference for the rapid application of intelligent and safe operation and maintenance technologies in the oil and gas industry.
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图 1 高端油气钻探装备组成及面临的难题挑战
Fig. 1. Composition and challenges of high-end oil and gas drilling equipment
图 2 智能安全运维实现流程
Fig. 2. Implementation process of intelligent security operation and maintenance
图 3 智能安全运维技术体系
Fig. 3. Intelligent security operation and maintenance technology system
图 4 钻井平台关键设备智能安全运维系统框架
Fig. 4. Framework of intelligent safety operation and maintenance system for key equipment of drilling platform
图 5 平台端关键设备全方位智能监测方案
Fig. 5. Comprehensive intelligent monitoring solution for key equipment on the platform
图 6 智能安全运维系统开发方案
a. 平台端和陆地端系统软件开发方案；b. 平台端系统技术架构；c. 陆地端系统技术架构
Fig. 6. Intelligent safety operation and maintenance system development scheme
图 7 智能安全运维系统的状态监测功能
a.主力发电机状态监测界面；b.主力发电机关键振动测点的振动烈度趋势图
Fig. 7. Condition monitoring functions of the intelligent safety operation and maintenance system
图 8 智能安全运维系统的故障诊断功能
a.钻井泵故障诊断界面；b. 相似度偏离程度；c. 磨损的钻井泵吸入阀阀体
Fig. 8. Fault diagnosis functions of the intelligent safety operation and maintenance system
图 9 智能安全运维系统的异常预警功能
a. 钻井异常工况判断界面；b. 异常双重判断条件
Fig. 9. Abnormal warning function of intelligent safety operation and maintenance system
图 10 智能安全运维系统的智能决策功能界面
Fig. 10. Intelligent decision-making function interface of intelligent safety operation and maintenance system
表 1 智能安全运维系统规模与关键配置
Table 1. Scale and key configuration of intelligent safety operation and maintenance system
配置项 参数/描述 覆盖设备 105台套 监测测点 216处 数据项总数 5 023项 采样频率 振动、电流：10 kHz；电子司钻数据：0.5 Hz 数据类型 连续型、布尔型、文本型 边缘端功能 实时数据采集、预处理、本地存储、实时报警、断网自治 云端功能 多源数据融合、健康评估、故障诊断、趋势预测、智能决策 通信方式 平台：光纤/Modbus/Profibus；平台-陆地：MQTT卫星通信 数据存储 边缘端：原始数据本地缓存30天；云端：历史数据长期存储 
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表 2 理论工程效益
Table 2. Theoretical engineering benefits
效益指标 主要计算依据 基线值 结果 平均故障间隔时间提升 关键设备故障率降低对系统整体故障率的贡献权重 17.5 d 提升15%~20%，达20~21 d 年度非计划停机时间减少 故障传播概率降低×平均修复时间 28 d 减少20%，降至24 d 年度维护相关成本降低 优化资源配置效率，减少突发维修及相关生产损失 / 成本降低8%~12%，节约约100万美元
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