Multivariate model for surface microseismic denoising in the shearlet domain

Mo Li; Fei Gao; Moli Wang; Yan Xu

doi:10.1117/12.2668272

23 February 2023 Multivariate model for surface microseismic denoising in the shearlet domain

Mo Li, Fei Gao, Moli Wang, Yan Xu

Proceedings Volume 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022); 125510W (2023) https://doi.org/10.1117/12.2668272
Event: Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 2022, Changchun, China

Abstract

Because of the strong random noise in surface microseismic data, the utility of the data may be decreased. Therefore, it is necessary to use some efficient techniques for denoising the microseismic data. Shearlet transform is a new multiscale transform which can adaptively capture the geometrical characteristic of multidimensional signals and represent signals containing edges optimally. Most traditional nonlinear thresholding methods based on Shearlet transform denoising presume that shearlet coefficients are independent. However, the shearlet coefficients of surface microseismic signals have significant dependencies. For this reason, these denoising schemes suppress too many coefficients that might contain useful microseismic signals information. We proposed a new multivariate model based on shearlet transform to improve this problem. This new multivariate model can not only adaptively capture the inter-scale dependency according to the anisotropic property of variances of shearlet coefficients in different sub-bands, but also take the inter-direction dependency into account. We perform tests on synthetic and field desert seismic data and the denoising results show that the proposed method can effectively preserve effective signals and remove random noise.

Citation Download Citation

Mo Li, Fei Gao, Moli Wang, and Yan Xu "Multivariate model for surface microseismic denoising in the shearlet domain", Proc. SPIE 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 125510W (23 February 2023); https://doi.org/10.1117/12.2668272

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KEYWORDS

Denoising

Interference (communication)

Signal to noise ratio

Data modeling

Multidimensional signal processing

Estimation theory

Signal attenuation

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