The reliability of microseismic moment-tensor solutions: Surface versus borehole monitoring

Abstract

Source mechanisms of microseismic events, resolved as moment-tensor solutions, usually are obtained using either surface monitoring arrays, which appear to obtain mechanisms with high shear components, or borehole arrays, which tend to constrain more variable mechanisms with higher tensile components; however, the corresponding reliability of the solutions remains unclear. Synthetic tests are therefore conducted to compare the reliability of moment-tensor solutions from surface and two- and three-well borehole arrays based purely on geometry. Moment-tensor inversion is carried out for synthetically generated amplitudes with added random noise, and the bias and variance in the solutions are calculated. For the surface array, all inversions are able to constrain reliable results (with negligible bias and low variance), whereas borehole geometries with two wells produce reliable results only when including P- and S-wave amplitudes recorded on three components in the inversion (as is usual). Surface array inversion results show less bias and variance in the results compared with borehole results, and the three-borehole geometry shows significantly lower biases and estimation variances than the two-borehole geometry, most likely due to a greater sampling of the focal sphere. These results may explain in part why downhole moment-tensor inversion studies tend to resolve more variable mechanisms than surface arrays. Nonetheless, as well as geometry, other influences (e.g., signal-to-noise ratio) will influence the reliability of the solutions in real settings and different amplitude strengths of pure shear or tensile mechanisms combined with different path lengths, and thus energy dissipation for borehole or surface acquisitions also may play a role. Nonetheless, tests such as those in this study are useful to help design appropriate monitoring geometries and/or understand possible sources of bias and uncertainty in moment-tensor interpretations.