Fine-scale ultralow-velocity zone structure from high-frequency seismic array data

Machine learning (ML) has proven its value in the seismic industry with successful implementations in areas of seismic interpretation such as fault and salt dome detection and velocity picking. The field of seismic processing research also is shifting toward ML applications in areas such as tomography, demultiple, and interpolation. Here, a supervised ML deblending algorithm is illustrated on a dispersed source array (DSA) data example in which both high- and low-frequency vibrators were deployed simultaneously. Training data pairs of blended and corresponding unblended data were constructed from conventional (unblended) data from another survey. From this training data, the method can automatically learn a deblending operator that is used to deblend for both the low- and the high-frequency vibrators of the DSA data. The results obtained on the DSA data are encouraging and show that the ML deblending method can offer a good performing, less user-intensive alternative to existing deblending methods.

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A High-Frequency Distance Metric in Ground-Motion Prediction Equations Based on Seismic Array Backprojections

Geophysical Research Letters ◽

10.1029/2018gl078930 ◽

2018 ◽

Vol 45 (21) ◽

pp. 11,612-11,621 ◽

Cited By ~ 2

Author(s):

Tian Feng ◽

Lingsen Meng

Keyword(s):

Ground Motion ◽

High Frequency ◽

Seismic Array ◽

Motion Prediction ◽

Ground Motion Prediction Equations ◽

Prediction Equations ◽

Distance Metric ◽

Ground Motion Prediction ◽

Frequency Distance

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Small-aperture seismic array data processing using a representation of seismograms at zero-crossing points

Physics of The Earth and Planetary Interiors ◽

10.1016/j.pepi.2018.04.010 ◽

2018 ◽

Vol 280 ◽

pp. 53-68 ◽

Cited By ~ 4

Author(s):

Johana Brokešová ◽

Jiří Málek

Keyword(s):

Data Processing ◽

Seismic Array ◽

Small Aperture ◽

Zero Crossing ◽

Array Data

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Detection capabilities of the Yellowknife seismic array and regional seismicity

Bulletin of the Seismological Society of America ◽

10.1785/bssa0610040993 ◽

1971 ◽

Vol 61 (4) ◽

pp. 993-1008

Author(s):

F. M. Anglin

Keyword(s):

Seismic Array ◽

Detection Level ◽

Array Data ◽

Regional Variations ◽

Regional Seismicity ◽

The Third ◽

Detection Capabilities ◽

The Mean

abstract Detection statistics from a search of 99 days of Yellowknife Array data have been obtained. The mean 50 and 90 per cent cumulative detection levels are found to be m 3.9 and m 4.2 for the third zone from Yellowknife. Regional variations in the detection levels have been found. The 50 per cent cumulative detection level ranges from m 3.8 for Asia to m 4.3 for the Aleutians. Regional values of the slopes of the recurrence curves for log N versus magnitude have been obtained, the mean slope for the third zone from Yellowknife being −0.99.

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