Abstract
The substantial volume of data acquired through remote-detection acoustic logging poses a remarkable challenge because of the limited real-time upload speed of the cable, which severely impedes its further application. To address this issue, a two-stage data compression method that was implemented at the acquisition node was proposed in this study. This approach includes a field programmable gate array (FPGA)-based hardware system and a two-stage downhole data compression algorithm combining wavelet transform and adaptive differential pulse-code modulation paired with ground decompression software. Finally, the proposed compression method was evaluated using actual logging data. The test results revealed that the overall compression rate of the two-stage compression method was 25.1%. The reconstructed waveforms highly retained the overall shape of the original waveforms, and the severe relative distortion of individual data points did not affect the extraction of the sliding longitudinal, sliding transverse and reflected waveforms. The FPGA compressed 2048 16-bit waveforms in approximately 100 μs with low resource utilization and workload. It considerably outperformed DSP-based pre-transmission compression. Herein, the data compression method at the acquisition node helped in reducing the workload on the master control node and increasing the effective speed of the cable transmission up to 400%, thereby enhancing the remote-detection acoustic logging.