Effect of noise on microseismic event detection and imaging using ICOVA statistical noise modelling method

Claire Birnie, Kit Chambers, Doug Angus, Anna Stork

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

Despite the evidence that noise does not conform to the White Gaussian Noise (WGN) assumption, the robustness
of new processing and imaging algorithms are still tested with WGN. This paper presents an alternative noise modelling method, based on multivariate statistics, to generate realistic noise for incorporation in synthetic datasets. The realistic noise model captures the complex nature of noise arising from multiple sources and the varying signal-to-noise (SNR) observed at the different stations across the array. This complex noise structure results in microseismic events being detected at lower SNR than would be implied using a WGN model. It also successfully re-creates smearing of energy during imaging of microseismic events at low SNRs. This modelling method provides an opportunity to test the robustness of new algorithms under realistic noise conditions prior to recording data in the field.
Original languageEnglish
Title of host publicationSEG Technical Program Expanded Abstracts 2016
PublisherSociety of Exploration Geophysicists, Tulsa, USA
Pages2622-2626
Number of pages5
DOIs
Publication statusPublished - 19 Oct 2016
EventSEG International Exposition and 86th Annual Meeting - Kay Bailey Hutchison Convention Center, Dallas, United States
Duration: 16 Oct 201621 Nov 2016
http://seg.org/Annual-Meeting-2016

Publication series

NameSEG Technical Program Expanded Abstracts 2016
PublisherSociety of Exploration Geophysicists
ISSN (Electronic)1949-4645

Conference

ConferenceSEG International Exposition and 86th Annual Meeting
CountryUnited States
CityDallas
Period16/10/1621/11/16
Internet address

Keywords

  • microseismic
  • statistical
  • passive imaging
  • modeling
  • noise

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