Automatic post processing algorithm for passive seismic monitoring data

Abstract A method to locate sound sources using an audio recording system mounted on an unmanned aerial vehicle (UAV) is proposed. The method introduces extension algorithms to apply on top of a baseline approach, which performs localisation by estimating the peak signal-to-noise ratio (SNR) response in the time-frequency and angular spectra with the time difference of arrival information. The proposed extensions include a noise reduction and a post-processing algorithm to address the challenges in a UAV setting. The noise reduction algorithm reduces influences of UAV rotor noise on localisation performance, by scaling the SNR response using power spectral density of the UAV rotor noise, estimated using a denoising autoencoder. For the source tracking problem, an angular spectral range restricted peak search and link post-processing algorithm is also proposed to filter out incorrect location estimates along the localisation path. Experimental results show the proposed extensions yielded improvements in locating the target sound source correctly, with a 0.0064–0.175 decrease in mean haversine distance error across various UAV operating scenarios. The proposed method also shows a reduction in unexpected location estimations, with a 0.0037–0.185 decrease in the 0.75 quartile haversine distance error.

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Towards fast DAS passive seismic monitoring combining Compressive Sensing with a deep learning decoder

10.3997/2214-4609.202131024 ◽

2021 ◽

Author(s):

I. Vera Rodriguez

Keyword(s):

Deep Learning ◽

Compressive Sensing ◽

Seismic Monitoring ◽

Passive Seismic

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Passive Seismic Monitoring and Integrated Geomechanical Analysis of a Tight-Sand Reservoir During Hydraulic-Fracture Treatment, Flowback and Production

Proceedings of the 2nd Unconventional Resources Technology Conference ◽

10.15530/urtec-2014-1929223 ◽

2014 ◽

Cited By ~ 8

Author(s):

David Eaton ◽

Mirko van der Baan ◽

Larry Matthews ◽

Enrico Caffagni

Keyword(s):

Hydraulic Fracture ◽

Seismic Monitoring ◽

Fracture Treatment ◽

Geomechanical Analysis ◽

Passive Seismic

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Remote Sensing Image Mosaic Algorithm

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.500.716 ◽

2012 ◽

Vol 500 ◽

pp. 716-721

Author(s):

Yi Ding Wang ◽

Shuai Qin

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Hot Spot ◽

Remote Sensing Image ◽

Processing Algorithm ◽

Geometric Features ◽

Image Mosaic ◽

Post Processing ◽

Remote Sensing Images ◽

Image Pixels

In the field of remote sensing, the acquirement of higher resolution of remote sensing images has become a hot spot issue with widely use of high resolution of remote sensing images. This paper focus on the characteristics of high resolution remote sensing images, on the basis of fully considerate of the correlation between geometric features and image pixels, bring forward a fusion of image mosaic processing algorithm. With this algorithm, the surface features can be well preserved after the processing of mosaic the remote sensing images, and the overlapping area can transit naturally, it will be better for the post-processing, analysis and application.

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