The MINE Project: Monitoring Induced Seismicity in a German Coal Mine

Abstract

AbstractDuring the last thee years, the MINE project has developed and successfully applied seismological tools, addressing different aspects of the monitoring of mining environments, as dynamic local-scale systems. The human interaction with the shallow underground mining environment, can lead to rock mass weakening or locally induce stress perturbations. As a consequence, triggered or induced seismicity is often observed at mines, potentially posing a risk to miners and infrastructures. This work illustrates a number of recently developed seismological techniques, based on the analysis of full waveforms, which target the problem of detection, location, and characterization of mining-induced seismicity. The proposed methodologies are here discussed through their application to a 14-months coal mining dataset, affecting the region of Hamm, Ruhr, Germany. An automated full-waveform detection and location technique is first used to generate a seismic catalog. A full moment tensor amplitude spectra technique is then adapted for the analysis of induced seismicity, leading to the inversion of more than 1000 focal mechanisms. Finally, a new developed clustering algorithm is used to automatically classify source types, and to track their temporal evolution. The combined application of the methods developed within the MINE project could successfully characterise the mining-induced seismicity and its spatio-temporal variation. Our methods are suitable for automated analysis, and can be easily adopted for mining monitoring purposes in other locations, and with different network geometries.KeywordsFocal MechanismMoment TensorMining EnvironmentMine ProjectMoment Tensor InversionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.