Predicting Rock Bursts in Rock Mass Blocks Using Acoustic Emission

• Published in: Resources
• Main Authors: Viktor V. Nosov, Alexey I. Borovkov, Artem P. Artyushchenko
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2022
• Subjects: rock burst risk; local forecast; acoustic emission; microfracture density; rock mass; forecasting; rock burst; core disking; Norilsk; norilsk
• Online Access: https://doi.org/10.3390/resources11100087

Geophysical methods for local rock burst prediction are currently being developed along two lines: improving recording equipment and improving data processing methods. Progress in developing processing methods is constrained by the lack of informative prognostic models that describe the condition of rock mass, the process of rock mass fracturing, and the phenomena that can substantiate the choice of both criteria and test parameters of the condition of rock mass and give an estimate of the time remaining until rock pressure manifestation. In particular, despite achievements in hardware design, researchers using the seismo-acoustic method to predict rock bursts measure the acoustical activity or energy capacity of elastic wave scattering after a man-made explosion and are faced with the dependence of forecast results on destabilizing factors. To solve this problem, we applied an information and kinetic approach to forecasting. In this article, we discuss the principles of selecting test parameters that are resistant to destabilizing factors. We propose a micromechanical model of fracture accumulation in a rock mass block that reflects the dependence of acoustic emission (AE) parameters on time, which makes it possible to detect the influence of various factors on forecast data and filter the signals. We also propose criteria and a methodology for rock burst risk assessment. The results were tested in analyzing the seismo-acoustic phenomena caused by man-made explosions at the Taimyrsky and Oktyabrsky mines in Norilsk. The article gives examples of using the proposed criteria. The effectiveness of their application is compared with traditional methods for assessing rock burst risks and evaluating the stress–strain parameters of rock mass in terms of their being informative, stable, and representative by means of statistical processing of experimental data.