Petroleum Science >2022, lssue 5: - DOI: https://doi.org/10.1016/j.petsci.2022.08.005
Automatic microseismic events detection using morphological multiscale top-hat transformation Open Access
文章信息
作者：Guo-Jun Shang, Wei-Lin Huang, Li-Kun Yuan, Jin-Song Shen, Fei Gao, Li-Song Zhao
作者单位：
投稿时间：
引用方式：Guo-Jun Shang, Wei-Lin Huang, Li-Kun Yuan, Jin-Song Shen, Fei Gao, Li-Song Zhao, Automatic microseismic events detection using morphological multiscale top-hat transformation, Petroleum Science, Volume 19, Issue 5, 2022, Pages 2027-2045, https://doi.org/10.1016/j.petsci.2022.08.005
文章摘要
Abstract: The occurrence of microseismic is not random but is related to the physical properties of the underground medium. Due to the low intensity and the influence of noise, microseismic eventually lead to poor signal-to-noise ratio. We proposed a method for automatic detection of microseismic events by adoption of multiscale top-hat transformation. The method is based on the difference between the signal and noise in the multiscale top-hat transform section and achieves the detection on a specific section. The microseismic data are decomposed into different scales by multiscale morphology top-hat transformation firstly. Then the potential microseismic events could be detected by picking up the peak value in the multiscale top-hat section, and the characteristic profile obtains the start point with a specific threshold value. Finally, the synthetic data experiences demonstrate the advantages of this method under strong and weak noisy conditions, and the filed data example also shows its reliability and adaptability.
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Keywords: Microseismic events detection; Multiscale morphology; Top-hat transformation