Identification of regionalized multiscale microseismic characteristics and rock failure mechanisms under deep mining conditions

Abstract

The rock mass failure induced by deep mining exhibits pronounced spatial heterogeneity and diverse mechanisms, with its microseismic responses serving as effective indicators of regional failure evolution and instability mechanisms. Focusing on the Level VI stope sublayers in the Jinchuan #2 mining area, this study constructs a 24-parameter index system encompassing time-domain features, frequency-domain features, and multifractal characteristics. Through manifold learning, clustering analysis, and hybrid feature selection, 15 key indicators were extracted to construct a classification framework for failure responses. Integrated with focal mechanism inversion and numerical simulation, the failure patterns and corresponding instability mechanisms across different structural zones were further identified. The results reveal that multiscale microseismic characteristics exhibit clear regional similarities. Based on the morphological features of radar plots derived from the 15 indicators, acoustic responses were classified into four typical types, each reflecting distinct local failure mechanisms, stress conditions, and plastic zone evolution. Moreover, considering dominant instability factors and rupture modes, four representative rock mass instability models were proposed for typical failure zones within the stope. These findings provide theoretical guidance and methodological support for hazard prediction, structural optimization, and disturbance control in deep metal mining areas.

1. Introduction

With the increasing depth and complexity of mineral resource exploitation, the combined effects of high in-situ stress, complex geological structures [1,2], and mining-induced disturbances have significantly raised the frequency of dynamic disasters in mines, posing serious threats to production safety [3,4]. Microseismic monitoring [5–7] has emerged as a crucial technique for identifying rock mass failure and energy release processes in deep mines. The waveform data not only capture the spatial and temporal evolution of failure events but also encode information about stress states, rupture mechanisms, and rock mass structures. However, due to the heterogeneity of rock mass constitutive properties, structural discontinuities, and uncertainties in mining disturbances, significant variations exist in microseismic triggering mechanisms, failure patterns, and nucleation region distributions across different types of engineered structures. These variations severely constrain scientific prevention and control of instability disasters in structurally complex deep mining environments [8–10].

In hard rock mines, particularly in deep stopes that adopt filling mining methods, multi-stage mining activities, evolving filling structures, and abrupt changes in excavation geometry lead to a complex interaction between stress fields and structural responses. In these conditions, microseismic activity often displays spatial clustering, a diversity of mechanisms, and intricate rupture paths, which inherently reflect the dominant failure processes associated with different structural domains. Therefore, it is crucial to investigate the multi-scale characteristics of microseismic waveforms and focal mechanisms in various structural zones to better understand their rupture behaviors and underlying instability mechanisms.

In recent years, numerous studies