Algorithm for calculating hazard areas of a rock massif based on geomechanical data

Abstract

Based on the analysis of existing approaches in the prediction of dynamic phenomena of rock pressure, it was established that the basis of most methods is the kinetic concept of the destruction of solids. A team of authors from the Mining Institute of the Far Eastern Branch of Russian Academy of Sciences has developed a method of geomechanical monitoring of a rock massif state, which consists of analyzing the dynamics of the acoustic active zones formation and predicting the impact hazard based on the established regularities of changes in the geoacoustic activity. This paper proposes an automated method for identifying focal zones, based on preliminary exclusion of background radiation using a non-parametric density estimation method, identifying seismoacoustic active zones by means of probabilistic cluster analysis and parameterizing focal zones by selecting a characteristic ellipsoid.

Research of the formation of zones of stress concentration and dynamic manifestations based on seismoacoustic monitoring data in the fields of the Kola Peninsula

“…Assessment of the geomechanical state of a rock mass based on seismoacoustic monitoring data using the automated rock pressure monitoring system (ARPMS) "Prognoz-ADS" is one of the most promising directions for predicting and preventing sudden destruction of rock structures, as well as rock and rock-tectonic impacts (man-made earthquakes), forecast and prevention of sudden destruction of pillars and mine workings [14][15][16][17][18]. ARPMS Prognoz-ADS is designed for continuous recording of seismoacoustic emission pulses in the frequency range of 0.5...12 kHz in a rock mass, determining their parameters (energy, coordinates, spectral and other characteristics of acoustic events) and presenting monitoring results in the form of catalogs, maps, graphs using modern 3D visualization software [19][20][21].…”

Designing an improved geoacoustic event location algorithm in the “Prognoz-ADS” system

“…This will make it possi ble to obtain a velocity map and to determine the eve nts c oordinates with a higher accurac y [12]. After time, data on the velocity d istribution will allo w no t only to in crease th e p erformance of h igh-precision location determination, but also to assess the rock massif state [13].…”

Regional prediction and prevention analysis of rockburst hazard based on the Gaussian process for binary classification

“…For the rockburst situation in Jixian Coal Mine, a GPC-based rockburst hazard prediction, prevention, and control technology system was established based on theoretical analysis (Iwata and Tanaka, 2022), and the intrinsic relationship between multiple influencing factors and rockburst was determined using a multifactor pattern identification method. By dividing the engineering area into prediction units and determining the pattern identification criteria and unit hazard probability values (Gladyr et al, 2021), the rockburst hazard area of the on-site engineering area was classified, and corresponding management measures were proposed (Wu et al, 2021b).…”