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Research on Two-Stage Data Compression at the Acquisition Node in Remote-Detection Acoustic Logging.

Xiaolong Hao1,2, Yangtao Hu1,2, Bingnan Yan1,2

  • 1Downhole Measurement and Control Laboratory of National Engineering Laboratory of Oil and Gas Drilling Technology, Xi'an 710065, China.

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|July 30, 2025
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Summary

A novel two-stage data compression method using FPGA hardware and wavelet transform significantly enhances remote-detection acoustic logging by achieving a 25.1% compression rate and boosting transmission speed up to 400%. This method preserves waveform integrity and outperforms existing techniques.

Keywords:
FPGAacoustic loggingadaptive differential pulse-code modulationtwo-stage data compressionwavelet transform

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Area of Science:

  • Geophysics
  • Data Science
  • Electrical Engineering

Background:

  • Remote-detection acoustic logging generates large data volumes, challenging real-time transmission due to limited cable upload speeds.
  • Existing data transmission methods are often inefficient for high-volume downhole data acquisition.

Purpose of the Study:

  • To develop and evaluate a two-stage data compression method for remote-detection acoustic logging data.
  • To improve real-time data transmission efficiency and reduce the workload on master control nodes.

Main Methods:

  • Implementation of a Field Programmable Gate Array (FPGA)-based hardware system at the acquisition node.
  • A two-stage downhole data compression algorithm combining wavelet transform and adaptive differential pulse-code modulation.
  • Development of ground decompression software for data reconstruction.

Main Results:

  • Achieved an overall data compression rate of 25.1% with the proposed method.
  • Reconstructed waveforms accurately retained the overall shape of original data, enabling effective extraction of seismic features.
  • The FPGA system compressed 2048 16-bit waveforms in approximately 100 μs with low resource utilization.
  • Demonstrated a 400% increase in effective cable transmission speed.

Conclusions:

  • The proposed FPGA-based two-stage data compression method effectively addresses the challenge of large data volumes in acoustic logging.
  • This approach significantly enhances the efficiency and applicability of remote-detection acoustic logging by improving data transmission speeds and reducing processing loads.