Optimization Research on Sensor Network Layout for Microseismic Monitoring Based on Location Error Analysis

Area of Science:

• Geophysics
• Mining Engineering
• Seismology

Background:

• Microseismic monitoring is vital for safety in deep underground mines.
• Optimizing sensor network geometry is key to accurate event localization.
• Existing methods often lack geometry-specific analysis for mine environments.

Purpose of the Study:

• To develop a numerical framework for optimizing microseismic sensor network layouts.
• To evaluate the impact of sensor geometry on localization accuracy and error distribution.
• To provide a reference for designing and refining mine-scale microseismic monitoring systems.

Main Methods:

• Developed a numerical framework for microseismic sensor network optimization.
• Evaluated three candidate deployment schemes using synthetic arrival-time perturbations.
• Applied the Geiger localization algorithm under varying uncertainty levels.
• Conducted event-wise robustness analysis to assess spatial enclosure and error.

Main Results:

• Localization performance is primarily determined by sensor layout geometry.
• Geometry dictates both the magnitude and spatial distribution of localization errors.
• The layout with the lowest overall error may not offer the best spatial enclosure.

Conclusions:

• Sensor network geometry is a critical factor in microseismic event localization.
• Findings offer a geometry-based approach for preliminary and refined design of mine monitoring systems.
• This study enhances understanding for deep underground engineering safety and monitoring.