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dc.contributor.author
Alexandrov, Dmitry
dc.contributor.author
Eisner, Leo
dc.contributor.author
Waheed, Umair bin
dc.contributor.author
Kaka, SanLinn I.
dc.contributor.author
Greenhalgh, Stewart Alan
dc.date.accessioned
2021-08-11T08:28:32Z
dc.date.available
2021-07-15T10:42:15Z
dc.date.available
2021-08-11T08:28:32Z
dc.date.issued
2020-11
dc.identifier.issn
0016-8033
dc.identifier.issn
1942-2156
dc.identifier.other
10.1190/GEO2019-0841.1
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/495052
dc.description.abstract
Microseismic monitoring aims at detecting as weak events as possible and providing reliable locations and source mechanisms for these events. Surface monitoring arrays suffer from significant variations of noise levels across receiver lines. When using a large monitoring array, we use a stacking technique to detect microseismic events through maximizing the signal-to-noise ratio (S/N) of the stack. But some receivers with a high noise level do not contribute to improving the S/N of the stack. We have derived a theoretical concept for the proper selection of receivers that best contribute to the stack for a constant strength of a signal across the array. This receiver selection criterion, based on the assumption of constant signal amplitude, provides a robust estimate of the noise threshold level, which could be used to discard or suppress contribution from the receivers that do not improve the S/N of the stack. We found that limiting the number of receivers for stacking improves the location accuracy and reduces the computational cost of data processing. Although the assumption of a constant signal never holds in real-life seismic applications, the noise level varies across the surface receivers in a significantly wider range than the signal amplitude. These noise variations can also increase the uncertainty of the source mechanism inversion and should be accounted for. Synthetic and field data examples show that weighted least-squares inversion with receiver weighting according to the noise level produces more accurate estimates for source mechanisms compared to the inversion that ignores information about noise.
en_US
dc.language.iso
en
en_US
dc.publisher
Society of Exploration Geophysicists
en_US
dc.title
Detection, location, and source mechanism determination with large noise variations in surface microseismic monitoring
en_US
dc.type
Journal Article
dc.date.published
2020-11-13
ethz.journal.title
Geophysics
ethz.journal.volume
85
en_US
ethz.journal.issue
6
en_US
ethz.pages.start
KS197
en_US
ethz.pages.end
KS206
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Tulsa
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2021-07-15T10:42:56Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-08-11T08:28:39Z
ethz.rosetta.lastUpdated
2022-03-29T11:00:44Z
ethz.rosetta.versionExported
true
ethz.COinS
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