An effective lossless compression method for attitude data with implementation on FPGA

Abstract

Abstract 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.

Keywords

• MWD
• Lossless compression
• Residual prediction
• Huffman coding
• FPGA