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Robustness of statistical algorithms for location of microseismic sources based on surface array data

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Abstract

Here, we present a statistical simulation study of several array data processing techniques used for the location of sources of elastic waves. The source location problem arises in such engineering applications as radio-communications, acoustics, sonar, meteorology, astrophysics, seismology, etcetera. Recently, this problem has become important for applied geophysics in connection with the modern technology of hydrocarbon production based on the hydraulic fracturing of the surface layers of the Earth’s environment. These techniques are required for the monitoring of hydraulic fracturing through the location of sources of numerous microearthquakes that occur during cracking of crustal rocks. We have established theoretical connections among several location algorithms. In particular, two different theoretical interpretations were proposed for the phase alignment location algorithm, recently proposed for the seismic array data processing. The robustness properties of the phase alignment location algorithm and the adaptive maximum likelihood location algorithm were demonstrated through Monte Carlo simulation in regard to variations of those noise statistical features, which are typical under monitoring of microseismicity at the hydrocarbon production sites. In the framework of the Monte Carlo modeling, we also compared the two mentioned location algorithms with the so-called emission tomography algorithm that is developed for the location of microseismic sources during the monitoring of hydraulic fracturing.

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Kushnir, A., Varypaev, A. Robustness of statistical algorithms for location of microseismic sources based on surface array data. Comput Geosci 21, 459–477 (2017). https://doi.org/10.1007/s10596-017-9623-6

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