Study on Gas–Solid Particle Dynamics and Optimal Drilling Parameters in Reverse Circulation DTH Drilling Based on CFD and Machine Learning

Abstract

The reverse circulation pneumatic down-the-hole (DTH) drilling system employs percussive drilling to achieve high efficiency and strong adaptability across diverse rock formations. However, its cutting removal efficiency remains suboptimal. To enhance reverse circulation performance, a comprehensive understanding of airflow and solid particle dynamics at the borehole bottom is essential. This study investigates rock cutting transportation and distribution under varying drilling parameters and evaluates reverse circulation flow ratio using a Computational Fluid Dynamics (CFD) multiphase flow model, coupled with finite volume analysis of the reverse circulation bit. Simulation results reveal that increasing the input gas flow rate (Q), reducing the equivalent particle diameter (D), and minimizing the borehole enlargement ratio (E) significantly improve cutting removal efficiency, with optimal values identified for each parameter. Additionally, solid volume fraction contours at the borehole bottom indicate that the arrangement of spherical teeth influences the flow field. Optimal values for rock cutting density (ρ), rate of penetration (ROP), and rotational speed (N) were also determined to maximize reverse circulation flow ratio. The Genetic Algorithm–Least Squares Support Vector Machine (GA-LSSVM) method was used to train the response surface data and construct a predictive model, which was then further optimized using Particle Swarm Optimization (PSO) to determine accurate parameter settings. These findings provide operational insights into optimizing drilling parameters to advance efficient drilling performance.