Lyu Fangxing, Xiong Zekang, Li Fei, Yue Ying, Zhang Nan
Xi'an Key Laboratory of Intelligent Equipment Development for Oil, Gas and Renewable Energy, Xi'an Shiyou University, Xi'an, 710065, Shaanxi, China.
Directional Drilling Laboratory of CNOOC Key Laboratory of Well Logging and Directional Drilling, Xi'an Shiyou University, Xi'an, 710065, Shaanxi, China.
Sci Rep. 2025 Apr 21;15(1):13809. doi: 10.1038/s41598-025-98372-7.
The attitude angles of the drilling tool serve as crucial information for transmitting Measurement While Drilling (MWD) data, enabling the optimization of drilling performance and ensuring tool safety. However, the real-time transmission and processing of attitude data pose a significant challenge, especially with the increasing prevalence of horizontal and directional drilling. To accurately and promptly obtain the attitude data, this paper proposes a lossless compression method based on Huffman coding, called Adaptive Frame Prediction Huffman Coding (AFPHC). This approach leverages the slowly varying characteristics of MWD tool attitude data, employing frame residual prediction to reduce data volume and selecting optimal bit widths for encoding transmission data. By using real-world drilling data, the proposed method is implemented on a Verilog HDL on a Xilinx field-programmable gate array (FPGA) circuit. Simulation and experiment results show that compression ratios provided by the proposed method for the inclination, azimuth, and toolface angles reach up to 4.02 times, 3.98 times, and 1.48 times, respectively, outperforming several existing methods.
钻井工具的姿态角是传输随钻测量（MWD）数据的关键信息，可实现钻井性能的优化并确保工具安全。然而，姿态数据的实时传输和处理面临重大挑战，尤其是随着水平井和定向钻井的日益普及。为了准确、及时地获取姿态数据，本文提出了一种基于哈夫曼编码的无损压缩方法，称为自适应帧预测哈夫曼编码（AFPHC）。该方法利用MWD工具姿态数据变化缓慢的特点，采用帧残差预测来减少数据量，并为编码传输数据选择最佳位宽。通过使用实际钻井数据，该方法在Xilinx现场可编程门阵列（FPGA）电路上以Verilog HDL实现。仿真和实验结果表明，该方法对倾斜角、方位角和工具面角的压缩比分别达到4.02倍、3.98倍和1.48倍，优于几种现有方法。
