Source parameter analysis using distributed acoustic sensing - an example with the PoroTomo array

In this study, I demonstrate that distributed acoustic sensing (DAS) raw strain rate data can directly be used to estimate spectral source parameters through an Empirical Green's Function (EGF) deconvolution analysis. Previously, DAS had been widely used in passive seismology to image the subsurface and analyze ground motion variations by converting strain or strain rate to particle velocity or acceleration prior to analysis. In this study, spectral analysis is applied to the PoroTomo joint DAS and seismic Nodal array in the Brady Hot Springs geothermal field to obtain source parameters for two M4 earthquakes via EGF analysis, where nearly collocated smaller events are used as an EGF to remove path and site effects. The EGF workflow is applied to raw DAS strain rate data without conversion to particle velocities and raw Nodal seismic data. The DAS and Nodal results are very consistent with similar features of spectral ratios, corner frequencies and moment ratios for the same event pairs. The uncertainty due to stacked spectral measurement is much lower on the DAS array, suggesting better stability of spectral shape measurement, possibly due to the much denser spatial sampling. The uncertainty due to model fitting is similar between DAS and Nodal arrays with slightly lower uncertainty on the DAS array. These observations demonstrate potential for directly using the strain rate measurements from DAS arrays for earthquake source characterizations.