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Synthesis of statistical algorithms for identifying of micro seismic source parameters using small aperture array observations

Varypaev Alexander Vyacheslavovich  (Moscow Institute of Electronics and Mathematics, Chair of advanced mathematics)

A problem of microsesmic source parameters estimation using surface wavefield observations obscured by random noise is considered. The maximum-likelihood estimate of parameters is proposed for case of unknown deterministic source function and noise correlated in time and space. It is shown that widely used seismic emission tomography is special case of maximum likelihood estimator under uncorrelated noise. A class of estimates based on observations phase information which are robust to noise properties is proposed. For particular case of estimation of source coordinates a subclass of phase algorithms is selected which are invariant to source radiation pattern. Using the method Monte-Karlo of independent trials significant advantage of estimation accuracy is demonstrated for proposed estimation techniques against existing approaches in conditions of strong man-made noise at hydrocarbon exploration sites.

Keywords:microseismic source, wave field, seismic moment tensor, maximum likelihood approach, spectral observations, phase robust estimators
 

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Citation link:
Varypaev A. V. Synthesis of statistical algorithms for identifying of micro seismic source parameters using small aperture array observations // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2012. -№12. -С. 21-36
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