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

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.