Effect of data filtering on source mechanisms inverted from surface microseismic monitoring array

The source mechanisms of induced microseismic events help understanding underground operations and mitigating hazards associated with induced seismicity. However, the uncertainty in the inverted source mechanisms is not well understood. In this study, we examine the impact of digital filters applied to dense surface monitoring data on the inverted source mechanisms derived from P-wave amplitudes. Ten filters, designed and used to increase signal to noise ratio, were tested. Filtering strongly affects both the shear and non-shear components of the full moment tensor. The differences in shear component orientation can exceed 20° in Kagan angle for some filters, despite the excellent coverage provided by the monitoring network. By constraining the inversion to pure shear mechanisms, the orientation was more stable. The smallest errors were observed with bandpass, interferometry, wavelet (with a well-chosen wavelet), and Wiener filters. On the other hand, the SVD and AGC filters resulted in largest changes in source mechanisms. Our results show that data filtering can lead to significant errors in the source mechanisms, which could potentially be misinterpreted if used to infer stress or other reservoir parameters.