Research and Improvement of Methods for Predicting Hidden Fracturing in a  Rock Mass at a Polymetallic Mine

N.B. Bakhtybayev; O.A. Abil; A.S. Bakhtybayeva

doi:10.31643/2028/6445.11

Authors

N.B. Bakhtybayev Mining Research Group LLP
O.A. Abil Mining Research Group LLP
A.S. Bakhtybayeva Mining Research Group LLP

DOI:

https://doi.org/10.31643/2028/6445.11

Keywords:

hidden fracturing, rock mass, underground mine workings, ground-penetrating radar profiling, laser scanning, fracture mapping, geomechanical modeling, mine support.

Abstract

This paper presents the results of a study aimed at improving the reliability of predicting hidden fracturing in the near-contour rock mass adjacent to underground mine workings at a polymetallic mine. The relevance of the study is associated with the fact that hidden discontinuities are not always identified during conventional visual inspection of the rock mass, which increases the risk of local collapses and complicates the selection of support parameters. The work aimed to improve methods for predicting hidden fracturing through the integrated application of ground-penetrating radar profiling, three-dimensional surveying, spatial fracture mapping, and geomechanical modeling. The study included analysis of the mining and geological conditions of the deposit, laser scanning of mine working sections, spatial fracture analysis in ShapeMetriX, numerical modeling in RocTunnel3, and GPR profiling using the GROT 12N system. It was established that the highest reliability of hidden fracturing prediction is achieved through the sequential integration of 3D survey data, spatial fracture analysis, and GPR investigation. The practical effect of the proposed approach lies in improving the validity of selecting existing support schemes rather than introducing new support types.

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Author Biographies

N.B. Bakhtybayev, Mining Research Group LLP

Candidate of Technical Sciences, Director of the Mining Research Group LLP, Karaganda, Kazakhstan. ORCID ID: https://orcid.org/0000-0002-9816-9765

O.A. Abil, Mining Research Group LLP

Executive Director of the Mining Research Group LLP, Karaganda, Kazakhstan. ORCID ID: https://orcid.org/0000-0001-9939-9039

A.S. Bakhtybayeva, Mining Research Group LLP

PhD, Senior researcher of the Mining Research Group LLP, Karaganda, Kazakhstan. ORCID ID: https://orcid.org/0000-0001-7163-6274

References

Butchibabu B, Sandeep N, Sivaram YV, Jha PC, Khan PK. Bridge pier foundation evaluation using cross-hole seismic tomographic imaging. Journal of Applied Geophysics. 2017; 144:104–114. https://doi.org/10.1016/j.jappgeo.2017.07.008

Hasan M, Shang Y, Meng Q. Application of electrical resistivity tomography (ERT) for rock mass quality evaluation. Scientific Reports. 2021; 11:24529. https://doi.org/10.1038/s41598-021-03217-8

Song Z, Zheng J, Zhang R, Zhu A, He T, Wang J. The potential of ground penetrating radar in rock fracture detection: insights from physical model tests and numerical simulations. Journal of Rock Mechanics and Geotechnical Engineering. 2025. https://doi.org/10.1016/j.jrmge.2025.04.036

Hunziker J, Greenwood A, Minato S, Barbosa ND, Caspari E, Holliger K. Bayesian full-waveform inversion of tube waves to estimate fracture aperture and compliance. Solid Earth. 2020; 11:657–668. https://doi.org/10.5194/se-11-657-2020

Ringel LM, Jalali M, Bayer P. Characterization of the highly fractured zone at the Grimsel Test Site based on hydraulic tomography. Hydrology and Earth System Sciences. 2022; 26:6443–6455. https://doi.org/10.5194/hess-26-6443-2022

Pavičić I, Galić I, Kucelj M, Dragičević I. Fracture system and rock-mass characterization by borehole camera surveying: application in dimension stone investigations in geologically complex structures. Applied Sciences. 2021; 11(2):764. https://doi.org/10.3390/app11020764

Hasan M, Shang Y, Meng Q. Evaluation of rock mass units using a non-invasive geophysical approach. Scientific Reports. 2023; 13:14493. https://doi.org/10.1038/s41598-023-41570-y

Huayllazo Y, Infa M, Frodella W, et al. Using electrical resistivity tomography method to determine the inner 3D geometry and the main runoff directions of the large active landslide of Pie de Cuesta in the Vitor Valley, Peru. Geosciences. 2023; 13(11):342. https://doi.org/10.3390/geosciences13110342

Rhee J-Y, Park K-T, Cho J-W, Lee S-Y. A study of the application and the limitations of GPR investigation on underground survey of the Korean expressways. Remote Sensing. 2021; 13(9):1805. https://doi.org/10.3390/rs13091805

Yuan W, Liu S, Zhao Q, Deng L, Lu Q, Pan L, Li Z. Application of ground-penetrating radar with the logging data constraint in the detection of fractured rock mass in Dazu Rock Carvings, Chongqing, China. Remote Sensing. 2023. 15(18):4452. https://doi.org/10.3390/rs15184452

Chen N, Hao Y, Wang C, Zheng J. Semi-automatic identification of discontinuity parameters in rock masses based on unmanned aerial vehicle photography. Geological Journal. 2024; 59(9):2401–2415. https://doi.org/10.1002/gj.4905

Liu Y, Hua W, Chen Q, Liu X. Characterization of complex rock mass discontinuities from LiDAR point clouds. Remote Sensing. 2024; 16:3291. https://doi.org/10.3390/rs16173291

Tomilov A, et al. Expert system for stability assessment of underground mine workings and automatic selection of rock bolt support schemes. Applied Sciences. 2025; 15(16):8951. https://doi.org/10.3390/app15168951

Isfahani NS, et al. Optimizing rock bolt support for large underground excavations in fractured rock masses using three-dimensional DEM-DFN modeling. Geosciences. 2025; 15(8):293. https://doi.org/10.3390/geosciences15080293

Zhang X, Pei J, Sha X, Feng X, Hu X, Chen C, Song Z. Experimental co-polarimetric GPR survey on artificial vertical concrete cracks by the improved time-varying centroid frequency scheme. Remote Sensing. 2024; 16(12):2095. https://doi.org/10.3390/rs16122095

Elshaboury N, Mohammed Abdelkader E, Al-Sakkaf A, Zayed T. A critical review and bibliometric analysis on applications of ground penetrating radar in science based on Web of Science database. Eng. 2023; 4(1):984–1008. https://doi.org/10.3390/eng4010059

Wang C, Liu Z, Dong Z, Zhang F, Ma C, Xu X, Guo Q. Comprehensive application of borehole fine detection methods: a case study in Shantou Bay subsea tunnel. Geofluids. 2024; 2024:5546191. https://doi.org/10.1155/2024/5546191

Research report Study on improving methods for predicting hidden fracturing of a rock mass. Karaganda: Mining Research Group LLP. 2026.

Salvini R, Rindinella A, Brogi A, et al. Stress–strain investigation of the rock mass based on overcoring with CSIRO HI cell test and numerical modeling: a case study from an Italian underground marble quarry. Geosciences. 2022; 12(12):441. https://doi.org/10.3390/geosciences12120441

Shi C, Yan X, Yang J, Liu Y. An inversion method for surrounding rock parameters of tunnels based on a probabilistic baseline model under a constructional environment. Geosciences. 2024; 14(4):107. https://doi.org/10.3390/geosciences14040107

Liu Y, Chen J, Zhan J. Revisiting each fracture size and spatial pattern: inference from rock mass surface to interior. Journal of Rock Mechanics and Geotechnical Engineering. 2025; 17(3):1399–1417. https://doi.org/10.1016/j.jrmge.2024.08.026

Technological regulations for selecting the types and parameters of support at the Dolinnoye mine. Version 3. 2025.