Publication Date:
2017-04-04
Description:
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.
Description:
Acknowledgments: We thank Schlumberger Cambridge Research for providing
funding for this project and for the hydrofracture surface monitoring
experiment. However, the views expressed here are those of the
authors, who are solely responsible for any errors. For the hydrofracture
surface data, we thank the Schlumberger office in Rock Springs, Wyoming,
for help with logistics and deployment, BP for permission to deploy seismometers
on one of their fields, Anna Horleston and Sharif Aboelnaga
for assistance in the field, and SEIS-UK for the loan of the seismometers.
The Cavola data were acquired by the Istituto Nazionale di Geofisica e
Vulcanologia, Italy. We thank the Cavola Experiment Team, particularly
John Haines (University of Cambridge), Giuliano Milana, Giuseppe Di
Giulio and Fabrizio Cara (Istituto Nazionale di Geofisica e Vulcanologia).
Ed Kragh and Everhard Muyzert provided helpful advice. University of
Cambridge, Department of Earth Sciences contribution No. ES9031.
Description:
Published
Description:
232-238
Description:
1.1. TTC - Monitoraggio sismico del territorio nazionale
Description:
N/A or not JCR
Description:
partially_open
Keywords:
seismic noise
;
Wiener filters
;
04. Solid Earth::04.06. Seismology::04.06.10. Instruments and techniques
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
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