Homomorphic deconvolution method based on adaptive variational mode decomposition
Ze1, PAN Shulin1, CHENG Yi2, GOU Qiyong3, WANG Chang3
1. School of Geoscience and Technology, Southwest Petroleum University, Chengdu, Sichuan 610500, China; 2. Research Institute of Petroleum Exploration and Development, Tuha Oil and Gas Field Company, PetroChina, Hami, Xinjiang 839009, China; 3. Shale Gas Research Institute, PetroChina Southwest Oil & Gas Field Company, Chengdu, Sichuan 610056, China
Abstract：Seismic waves are affected by earth low-pass filtering during their propagation in strata，which greatly reduces the resolution. Deconvolution processing can improve the resolution of seismic data. The homomorphic deconvolution method has no requirement for wavelet phase and is more applicable. However，in actual proces-sing，wavelets and reflection coefficients are difficult to completely separate in a homomorphic domain. To solve this problem，this paper proposes using a variational mode decomposition (VMD) method to separate wavelets and re-flection coefficients in a homomorphic domain. The method improves the anti-noise ability of homomorphic deconvolution. Firstly, homomorphic transformation is performed on seismic records to obtain the data of a homomorphic domain. Then VMD is performed on the data，and specific decomposed data are selected for reconstruction to eliminate the influence of wavelets. Finally, the reflection coefficient sequence is recovered by the inverse homomorphic transformation of the reconstruction results. Considering that the VMD method cannot directly determine the decomposition levels, the paper uses a method based on the energy difference between the reconstructed data and the original data to automatically determine the decomposition level，which greatly improves the effect of the VMD method. Synthetic data experiments show that the method can still obtain ideal calculation results in the case of a time-varying wavelet and a low signal-to-noise ratio. Using this algorithm to process actual seismic data and extract seismic attributes can effectively improve the lateral resolution of actual data and achieve a good application effect.
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