Abstract：Microseismic monitoring is widely applied in unconventional oil and gas fields, and supports the production and reserve increase of oil and gas fields. Because microseismic data are non-stationary, conventional denoising methods are not effective. This paper proposes a time-frequency peak filtering (TFPF) method of adaptive white noise based on the sample entropy (SE) complete set of empirical mode decomposition (CEEMDAN) to suppress noises while preserving effective signals. First raw microseismic data are decomposed into several IMFs of intrinsic modal components by CEEMDAN. Then after calculating the sample entropy, the IMFs are divided into two groups — one group will be filtered and the other will be left alone. The former group is TFPF filtered after selecting filter windows, and reconstructed with the latter to get final filtered signals. Application to theoretical model and field data has shown that the noise suppression method proposed in the paper is more effective than traditional EMD and constant-window TFPF denoising methods.
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