地质钻探专家决策系统开发与信息化发展路径分析

Development of an expert decision-making system for geological drilling and analysis of informatization pathways

摘要:

针对地质钻探工程中数据采集标准化缺失、决策分析维度单一、数据价值挖掘不足等问题，本文提出了一套基于物联网与人工智能技术的钻探专家决策系统。系统通过构建多源数据采集层、混合存储架构、实时计算引擎与可视化前端技术，实现了钻井参数实时监测、工况自动识别与专家在线反馈功能，以期为提升钻探安全性与时效性、降低井内事故率提供支撑。下一步，将融合知识图谱与生成式大模型技术，构建“透明井下-智能井场-云端大脑”三级智能决策体系，推动地质钻探从“经验驱动”向“数据智能”范式跃迁。

Abstract:

To address challenges in geological drilling engineering， such as non-standardized data acquisition， single-dimensional decision analysis， and insufficient data value utilization， this study proposes an expert decision-making system based on IoT and artificial intelligence （AI） technologies. The system integrates a multi-source data acquisition layer， a hybrid storage architecture， a real-time computing engine， and a visualization frontend， enabling real-time monitoring of drilling parameters， automated operating condition recognition， and expert feedback， with which to enhance drilling safety and operational efficiency while providing robust support for reducing downhole accident rates. Future work will focus on integrating knowledge graph and generative large language model technologies to establish a three-tier intelligent decision-making framework （“transparent downhole-smart wellsite-cloud brain”）， driving the paradigm shift from “experience-driven” to “data-intelligent” geological drilling.