Abstract

ABSTRACT Downhole distributed acoustic sensing (DAS) data are now routinely acquired on fiber-optic cables deployed in wells for seismic imaging and microseismic monitoring. We develop a semiempirical workflow for estimating scalar seismic moment and moment magnitude of earthquakes using strain data recorded by downhole DAS arrays. At far-field distances, the time integral of axial strain is proportional to the displacement scaled by apparent slowness. Therefore, seismic moment can be directly estimated from the amplitude of the low-frequency plateau of the strain spectra divided by frequency, similar to the methodology commonly employed for far-field displacement spectra. The effect of polarization on strain amplitudes for different types of body waves is accounted for. Benefitting from the large spatial coverage provided by DAS arrays, moment estimates from multiple channels are averaged and an average radiation coefficient is assumed over the focal sphere. We validate the methods using data of microseismic events simultaneously recorded by a surface geophone array and by DAS on fiber deployed in two horizontal wells during a hydraulic fracturing experiment. For 106 microseismic events in the magnitude range ∼ −0.65 to ∼ +0.55, we find the DAS-derived magnitudes to be consistent with the magnitudes derived from the geophone array using traditional methods, with ∼95% of the magnitude estimates differing by less than ∼0.26 units. The workflow can be potentially extended to DAS arrays in vertical wells and to S waves recorded on dark fiber DAS arrays at the surface. This methodology does not require any calibration beyond knowledge of local seismic properties, and the use of the lowest possible frequencies reduces the influence of subsurface heterogeneities and the finite spatiotemporal extent of earthquake ruptures. The capacity to estimate robust seismic magnitudes from downhole DAS arrays allows improved evaluation and management of fracture growth and more effective mitigation of induced seismicity.

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