White, R. S.

We are concerned with the detection and location of small seismic events, such as can be encountered in monitoring hydro-fracturing with surface sensors. Ambient seismic noise is the main problem in detection of weak seismic phases from these events, particularly as the sites of interest are often within or near producing fields. Band-pass filtering and stacking are the most widely used techniques for enhancing the signal-to-noise ratio (SNR) in passive seismic experiments, but they are of limited value when noise and signal share the same frequency band. Seismic arrays can be used to reduce the unwanted noise (e.g., traffic noise, pumping noise, scattering ground roll) by delay-and-sum techniques (also called beamforming) or by frequencywavenumber filtering. Beamforming maximizes the array response for the assumed direction and slowness of the signal. Whereas in some situations it can be highly effective, and the azimuth and slowness of the signal can be determined by a grid search approach, it is vulnerable to contamination by side-lobe energy, particularly for broadband signals and noise (Rost and Thomas, 2002). Frequencywavenumber filtering can be very effective but requires regularly spaced arrays and implicitly assumes plane-wave propagation. Both methods perform poorly when the waveform changes significantly between stations of the array, as might be caused, for example, by differences in site response. In this article, we present a multichannel Wiener filtering technique, which allows the removal of coherent noise from three-component 2D arrays without making a priori assumptions about the mode of propagation (e.g., no planewave assumption is required for the noise field). We test the effectiveness of this filter with two case studies. In the first case, we add synthetic signals of varying strengths to actual noise data recorded with a hexagonal array during hydrofracturing within a producing oil field in Wyoming, USA. Using this test, we are able to provide estimates of the smallest event detectable with the filtered data, and compare the results with conventional techniques, such as stacking. The second test case is a dense, small-aperture 2D seismic array of 95 stations placed within an area of 130 m 56 m on a landslide deposit in the Northern Apennines, Italy. Numerous microearthquakes have been recorded with this array, whose faint P-phases serve as an ideal data set for testing filtering techniques. Using the two case studies, we discuss the effectiveness of the multichannel Wiener filter on SNR improvement, and show that including horizontal components into the analysis increases the SNR improvement more than using only vertical components.

Hydraulic-fracture induced microseismic events are usually small, and noise levels are high at the surface due to the activities associated with a producing oil field. Similarly, local arrays for the detection of local earthquakes will also benefit from reduced noise levels and detect smaller events. We present a frequency-dependent multi-channel Wiener filtering technique with linear constraints, which employs an adaptive least-squares technique to remove coherent noise in seismic array data. The noise records on a number of reference channels is used to predict the noise on a primary channel, which can then be subtracted. We implement and test first an unconstrained version of this filter, where maximal noise suppression can lead to signal distortion. Two methods of imposing constraints are then introduced to achieve signal preservation. We test this technique with two case studies. First, synthetic signals are added to actual noise from a pilot deployment of a hexagonal array (9 three-component seismometers, approximate size 150 m × 150 m) in an oil field; noise levels are suppressed by up to 11 dB (at 1 - 6 Hz). Secondly we use natural seismicity recorded at a dense array (∼10 m spacing) in Italy where the application of the filter reduces the signal-to-noise ratio by more than 20 dB (at 8 - 15 Hz), using 35 stations. In both cases, the performance of the multi-channel Wiener filters is significantly better than stacking, especially at lower frequency where stacking does not help to suppress the coherent noise. The unconstrained version of the filter yielded the best improvement in the signal-to-noise ratio, but the constrained filter is useful when waveform distortion is not acceptable.