An effective noise-suppression technique for surface microseismic data

Farnoush Forghani-Arani, Mark Willis, Seth S. Haines, Mike Batzle, Jyoti Behura, Michael Davidson

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


The presence of strong surface-wave noise in surface microseismic data may decrease the utility of these data. We implement a technique, based on the distinct characteristics that microseismic signal and noise show in the τ-p domain, to suppress surface-wave noise in microseismic data. Because most microseismic source mechanisms are deviatoric, preprocessing is necessary to correct for the nonuniform radiation pattern prior to transforming the data to the τ-p domain. We employ a scanning approach, similar to semblance analysis, to test all possible double-couple orientations to determine an estimated orientation that best accounts for the polarity pattern of any microseismic events. We then correct the polarity of the data traces according to this pattern, prior to conducting signal-noise separation in the τ-p domain. We apply our noise-suppression technique to two surface passive-seismic data sets from different acquisition surveys. The first data set includes a synthetic microseismic event added to field passive noise recorded by an areal receiver array distributed over a Barnett Formation reservoir undergoing hydraulic fracturing. The second data set is field microseismic data recorded by receivers arranged in a starshaped array, over a Bakken Shale reservoir during a hydraulicfracturing process. Our technique significantly improves the signal-to-noise ratios of the microseismic events and preserves the waveforms at the individual traces. We illustrate that the enhancement in signal-to-noise ratio also results in improved imaging of the microseismic hypocenter.

Original languageEnglish
Pages (from-to)KS85-KS95
Issue number6
StatePublished - 2013


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