Ground Motion Prediction of High-Energy Mining Seismic Events: A Bootstrap Approach

Piotr Bańka, Adam Lurka () and Łukasz Szuła
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Piotr Bańka: Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, Akademicka 2A, 44-100 Gliwice, Poland
Adam Lurka: Laboratory of Mining Geophysics, Central Mining Institute, Plac Gwarkow 1, 40-166 Katowice, Poland
Łukasz Szuła: Polish Mining Group, Powstancow 30, 40-039 Katowice, Poland

Energies, 2023, vol. 16, issue 10, 1-15

Abstract: Induced seismicity has been a serious problem for many coal mines in the Upper Silesian Coal Basin in Poland for many decades. The occurring mining tremors of the rock mass generate seismic vibrations that cause concern to the local population and in some rare cases lead to partial damage to buildings on the surface. The estimation of peak ground acceleration values caused by high energy mining seismic tremors is an important part of seismic hazard assessment in mining areas. A specially designed bootstrapping procedure has been applied to estimate the ground motion prediction model and makes it possible to calculate the confidence intervals of these peak ground acceleration values with no assumptions about the statistical distribution of the recorded seismic data. Monte Carlo sampling with the replacement for 132 seismic records measured for mining seismic tremors exceeding 150 mm/s 2 have been performed to estimate the mean peak ground acceleration values and the corresponding upper limits of 95% confidence intervals. The specially designed bootstrap procedure and obtained ground motion prediction model reflect much better the observed PGA values and therefore provide more accurate PGA estimators compared to the GMPE model from multiple regression analysis. The bootstrap analysis of recorded peak ground acceleration values of high-energy mining tremors provides significant information on the level of seismic hazard on the surface infrastructure. A new tool has been proposed that allows for more reliable determination of PGA estimators and identification in the areas in coal mines that are prone to high-energy seismic activity.

Keywords: underground coal mine; mining-induced seismicity; mining seismology; ground motion prediction equations; seismic hazard; peak ground acceleration; Monte Carlo method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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