Abstract
The resolution of seismic data determines the ability to characterize stratigraphic features from observed seismic records. Sparse spike inversion, as an important processing method, can effectively improve the band-limited property of the seismic data. However, this approach ignores the spatial information along seismic traces, which causes the unreliability of the reconstructed high-resolution data. In this paper, we develop a high-frequency structure-constrained multichannel deconvolution (HFSC-MD) to alleviate this issue. This method allows the cost function to incorporate high-frequency spatial information in the form of a prediction-error filter (PEF) to regularize the components of the result beyond the original frequency. The PEF, also called a high-frequency reflection structural characterization operator, is estimated from the mapping relationship of low- and high-frequency components. We adopt the alternating direction method of multipliers to solve the cost function in HFSC-MD. Synthetic and field data demonstrate that our method recovers more reliable high-resolution data and enriches reflective structures.
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