基于人工智能的钻速系统优化研究

Intelligent drilling is a hot topic in recent years. Accurate rate of penetration (ROP) prediction and optimization is an essential research field in drilling engineering. However, most of the existing research achievements are still in the theoretical research stage, which lack of a unified data processing framework and actual application test. This paper proposes a ROP optimization framework based on artificial intelligence algorithm. It integrates five parts, namely, intelligent control module, data management module, data preprocessing module, ROP prediction module and ROP optimization module. It can effectively regulate the real-time transmission and storage of drilling data. It also integrates the existing ROP prediction and optimization algorithm, which providing reliable reference for the field drilling platform. Through the field test, the effectiveness and real-time performance of ROP optimization framework are verified.