Generalized Free-surface effect and random vibration theory: A new tool for computing moment magnitudes of small earthquakes using borehole data

Abstract

Although optimal, computing the moment tensor solution is not always a viable option for the calculation of the size of an earthquake, especially for small events (say, below Mw 2.0). Here we show an alternative approach to the calculation of the moment-rate spectra of small earthquakes, and thus of their scalar moments, that uses a network-based calibration of crustal wave propagation. The method works best when applied to a relatively small crustal volume containing both the seismic sources and the recording sites. In this study we present the calibration of the crustal volume monitored by the High-Resolution Seismic Network (HRSN), along the San Andreas Fault (SAF) at Parkfield. After the quantification of the attenuation parameters within the crustal volume under investigation, we proceed to the spectral correction of the observed Fourier amplitude spectra for the 100 largest events in our data set. Multiple estimates of seismic moment for the all events (1811 events total) are obtained by calculating the ratio of rms-averaged spectral quantities based on the peak values of the ground velocity in the time domain, as they are observed in narrowband-filtered time-series. The mathematical operations allowing the described spectral ratios are obtained from Random Vibration Theory (RVT). Due to the optimal conditions of the HRSN, in terms of signal-to-noise ratios, our network-based calibration allows the accurate calculation of seismic moments down to Mw < 0. However, because the HRSN is equipped only with borehole instruments, we define a frequency-dependent Generalized Free-Surface Effect (GFSE), to be used instead of the usual free-surface constant F = 2. Our spectral corrections at Parkfield need a different GFSE for each side of the SAF, which can be quantified by means of the analysis of synthetic seismograms. The importance of the GFSE of borehole instruments increases for decreasing earthquake's size because for smaller earthquakes the bandwidth available for our calculations is consistently shifted towards higher frequencies.