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Post-stack processing technology and application of EMD deconvolution combined with structure-orientation constrained filtering |
SHAO Jia, WU Furong, LIU Zhigang, ZHANG Jinglei, ZHOU Chang, ZHAO Mingkun |
Southwest Geophysical Research Institute, BGP Inc., CNPC, Chengdu, Sichuan 610213, China |
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Abstract Seismic signals are a kind of non-stationary signals, and as the time variability of seismic wavelet has been puzzling seismic data processing, it is necessary to adopt adaptive analysis methods to extract the local feature information of non-stationary seismic signals.The empirical mode decomposition (EMD) is employed to decompose seismic signals, and the local characteristic information of the signal can be extracted.The intrinsic mode functions (IMFs) obtained by the signal through EMD are not affected by external factors, and the decomposition number is completely determined by the original signal itself.Therefore, the EMD method has complete adaptability and is a good method for analyzing non-stationary seismic signals.The resolution of 3D seismic data is improved by combining EMD deconvolution and structure-oriented constrained filtering.EMD deconvolution technology decomposes seismic signals into a finite number of IMFs through the EMD algorithm, improves the resolution of each IMF through deconvolution processing, and enhances the overall resolution by reconstructing seismic signals.Meanwhile, it can better maintain the signal-to-noise ratio, relative amplitude relationship, and time-frequency characteristics of seismic data.The noise of EMD deconvolution data can be filtered by structure-oriented constrained filtering technology, and the signal-to-noise ratio of seismic data can be improved.The reservoir prediction results are in agreement with the drilling data.The application results of the proposed method in JL region are as follows.①The combination of post-stack EMD deconvolution and structure-oriented constrained filtering can improve the seismic resolution with a large frequency band width of seismic data, while maintaining a high signal-to-noise ratio.②The reservoir prediction results match the real drilling results and are more in line with geological understanding, with the reservoir prediction accuracy higher than the original seismic data.
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Received: 19 October 2022
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