Microseismic events enhancement and detection in sensor arrays using autocorrelation‐based filtering |
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| Authors: | Entao Liu Lijun Zhu Anupama Govinda Raj James H McClellan Abdullatif Al‐Shuhail SanLinn I Kaka Naveed Iqbal |
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| Institution: | 1. Center for Energy and Geo Processing (CeGP), Georgia Institute of Technology, Atlanta, USA;2. King Fahd University of Petroleum and Minerals, Saudi Arabia |
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| Abstract: | Passive microseismic data are commonly buried in noise, which presents a significant challenge for signal detection and recovery. For recordings from a surface sensor array where each trace contains a time‐delayed arrival from the event, we propose an autocorrelation‐based stacking method that designs a denoising filter from all the traces, as well as a multi‐channel detection scheme. This approach circumvents the issue of time aligning the traces prior to stacking because every trace's autocorrelation is centred at zero in the lag domain. The effect of white noise is concentrated near zero lag; thus, the filter design requires a predictable adjustment of the zero‐lag value. Truncation of the autocorrelation is employed to smooth the impulse response of the denoising filter. In order to extend the applicability of the algorithm, we also propose a noise prewhitening scheme that addresses cases with coloured noise. The simplicity and robustness of this method are validated with synthetic and real seismic traces. |
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| Keywords: | Passive seismic Denoising Detection Sensor array Autocorrelation Filter design |
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