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    • Multichannel Deconvolution with Spatial Reflection Regularization

    Hao Li,Guo-Fa Li,Xiong Ma,Jia-Liang Zhang, Qing-Long Meng, Zhu-Xin Zhang

    Applied Geophysics（2021）

    China University of Petroleum

    Cited 4|Views5
    Abstract
    Seismic deconvolution plays an important role in the seismic characterization of thin-layer structures and seismic resolution enhancement. However, the trace-by-trace processing strategy is applied and ignores the spatial connection along seismic traces, which gives the deconvolved result strong ambiguity and poor spatial continuity. To alleviate this issue, we developed a structurally constrained deconvolution algorithm. The proposed method extracts the reflection structure characterization from the raw seismic data and introduces it to the multichannel deconvolution algorithm as a spatial reflection regularization. Benefiting from the introduction of the reflection regularization, the proposed method enhances the stability and spatial continuity of conventional deconvolution methods. Synthetic and field data examples confirm the correctness and feasibility of the proposed method.
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    Key words
    Deconvolution,spatial reflection regularization,resolution,sparse-spike
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