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

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.