To improve the operational efficiency of the dynamic point-the-bit rotary steerable system (DPB-RSS) in deep and complex formations, this paper proposes a build-up rate (BUR) prediction model, a trajectory control model, and a mechanism–data fusion model for rate of penetration (ROP) prediction. Validation using field data from Well A indicates that the BUR and ROP models achieve prediction accuracies of 91.45% and 91.34%, respectively, demonstrating the reliability of the proposed models. Based on the validated models, a parameter sensitivity analysis was conducted for Well B to investigate the effects of weight on bit (WOB), rotary speed, and flow rate on drilling performance, thereby identifying a recommended operational parameter combination (WOB ≥ 60 kN, rotary speed = 105 rpm, and flow rate = 65 L/s). In addition, well trajectory control was implemented by dynamically adjusting the tool face angle and steering ratio using a compound control algorithm. Field application results further indicate that the proposed scheme can improve tool performance and provide useful guidance for efficient drilling with DPB-RSS.
Zhang et al. (Wed,) studied this question.