Modeling of the Nano- and Picoseismicity Rate Changes Resulting from Static Stress Triggering due to Small (MW2.2) Event Recorded at Mponeng Deep Gold Mine, South Africa
Friday, 19 December 2014: 11:20 AM
Static stress changes following large earthquakes are known to affect the rate and spatio-temporal distribution of the aftershocks. Here we utilize a unique dataset of M ≥ -3.4 earthquakes following a MW 2.2 earthquake in Mponeng gold mine, South Africa, to investigate this process for nano- and pico- scale seismicity at centimeter length scales in shallow, mining conditions. The aftershock sequence was recorded during a quiet interval in the mine and thus enabled us to perform the analysis using Dietrich’s (1994) rate and state dependent friction law. The formulation for earthquake productivity requires estimation of Coulomb stress changes due to the mainshock, the reference seismicity rate, frictional resistance parameter, and the duration of aftershock relaxation time. We divided the area into six depth intervals and for each we estimated the parameters and modeled the spatio-temporal patterns of seismicity rates after the stress perturbation. Comparing the modeled patterns of seismicity with the observed distribution we found that while the spatial patterns match well, the rate of modeled aftershocks is lower than the observed rate. To test our model, we used four metrics of the goodness-of-fit evaluation. Testing procedure allowed rejecting the null hypothesis of no significant difference between seismicity rates only for one depth interval containing the mainshock, for the other, no significant differences have been found. Results show that mining-induced earthquakes may be followed by a stress relaxation expressed through aftershocks located on the rupture plane and in regions of positive Coulomb stress change. Furthermore, we demonstrate that the main features of the temporal and spatial distribution of very small, mining-induced earthquakes at shallow depths can be successfully determined using rate- and state-based stress modeling.