Dynamic stress characterization and instability risk identification using multisource acoustic signals in...

Area of Science:

• Geotechnical Engineering
• Mining Seismology
• Rock Mechanics

Background:

• Quantitative characterization of rock mass and stress changes is vital for structural stability monitoring and disaster early warning in mining operations.
• Pillar-free large-area continuous extraction presents unique challenges for understanding rock mass behavior and stress evolution.
• Microseismic monitoring is essential for assessing the dynamic response of rock masses to mining activities.

Purpose of the Study:

• To investigate the spatiotemporal distribution of microseismic sources during pillar-free large-area continuous extraction.
• To develop and apply a method combining velocity field and spatial b-value patterns for identifying stress and structural changes in panel stopes.
• To enhance the identification of instability disasters by analyzing anomalous wave velocities and b-values.

Main Methods:

• Analysis of time-space-intensity distribution of microseismic sources.
• Collaborative evolution pattern analysis of velocity fields and spatial b-values.
• Identification of anomalous zones in wave velocities and b-values at critical geological structures and mining interfaces.

Main Results:

• Anomalous zones in wave velocities and b-values were identified at intersections of mining roadways and footwall ore-rock contacts, correlating with microseismic event nucleation.
• The synergistic use of velocity fields and spatial b-values effectively revealed stress migration and stope structure changes induced by mining.
• An instability disaster at a connection roadway and cross-drift intersection was successfully identified through increased wave velocity and abnormal b-value changes.

Conclusions:

• The combined analysis of wave velocity fields and spatial b-values provides a robust method for characterizing stress and structural changes in mining environments.
• This approach offers valuable insights for predicting geotechnical engineering disasters in complex stress conditions.
• The findings support the potential of this method for real-time risk identification and structural stability monitoring in underground mining.