Application of frequency-dependent multichannel Wiener filters to detect events in 2D three-component seismometer arrays

摘要

Hydraulic fracture-induced microseismic events in producing oil and gas fields are usually small, and noise levels are high at the surface as a result of the heavy equipment in use. Similarly, in nonhydrocarbon settings, arrays for detecting local earthquakes will benefit from reduced noise levels and the ability to detect smaller events will be increased.We propose a frequency-dependent multichannel Wiener filtering technique with linear constraints that uses an adaptive least-squares method to remove coherent noise in seismic array data. The noise records on several reference channels are used to predict the noise on a primary channel and then can be subtracted from the observed data. On a test with an unconstrained version of this filter, maximal noise suppression leads to signal distortion. Two methods of imposing constraints then achieve signal preservation. In one case study, synthetic signals are added to noise from a pilot deployment of a hexagonal array nine three-component seismometers, approximately 150150 m above a gas field; noise levels are suppressed by up to 11 dB at 2–10 Hz. In a second case study, natural seismicity recorded at a dense array 10 m spacing in Italy is used, where the application of the filter improves the signal- to-noise ratio S/N more than 20 dB at 2–15 Hzusing 35 stations. In both cases, the performance of the multichannel Wiener filters is significantly better than stacking, especially at lower frequencies where stacking does not help to suppress the coherent noise. The unconstrained version of the filter yields the best improvement in signal-to-noise ratio, but the constrained filter is useful when waveform distortion is unacceptable.