Journal
JOURNAL OF APPLIED GEOPHYSICS
Volume 132, Issue -, Pages 116-124Publisher
ELSEVIER
DOI: 10.1016/j.jappgeo.2016.06.008
Keywords
Short time Fourier transform; Seismic denoising; Microseismic detection; Noise estimation
Funding
- Air Force Research Laboratory [FA9453-16-C-0015]
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Microseismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. A noise level estimation and noise reduction algorithm is presented for microseismic data analysis based upon minimally controlled recursive averaging and neighborhood shrinkage estimators. The method might not be compared with more sophisticated and computationally expensive denoising algorithm in terms of preserving detailed features of seismic signal. However, it is fast and data-driven and can be applied in real-time processing of continuous data for event detection purposes. Results from application of this algorithm to synthetic and real seismic data show that it holds a great promise for improving microseismic event detection. (C) 2016 Elsevier B.V. All rights reserved.
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