High-speed real-time periodic weak pulse signal detection with simplified phase-weighted stacking

Area of Science:

• Exploration Seismology
• Signal Processing
• Geophysics

Background:

• Phase-weighted stacking (PWS) is crucial for noise reduction in seismic exploration.
• Existing PWS methods face computational challenges for real-time weak signal detection.
• High repetition frequency signals require efficient processing techniques.

Purpose of the Study:

• To develop a simplified PWS method with reduced computational complexity.
• To enable real-time detection of weak periodic pulse signals.
• To enhance the signal-to-noise ratio (SNR) in seismic data processing.

Main Methods:

• A novel simplified PWS algorithm dividing the complex plane into four quadrants.
• Simplifying instantaneous phases within the same quadrant.
• Integration with a one-bit analog-to-digital converter and FPGA for real-time processing.

Main Results:

• The simplified PWS algorithm improves SNR by 10-15 dB for weak pulse signals (-21 dB to -15 dB SNR).
• Achieved a low latency of approximately 2 µs for real-time detection.
• A prototype successfully verified the proposed technique's effectiveness.

Conclusions:

• The simplified PWS method offers a computationally efficient solution for real-time weak signal detection.
• This technique significantly enhances SNR in seismic data, aiding exploration.
• The FPGA-based implementation enables high-speed, low-latency signal processing.