A high-resolution method of spectral fitting with horizon constraints and its application

Abstract When seismic waves propagate underground, subsurface media can absorb high-frequency components of the seismic waves, resulting in attenuation of the high-frequency portion of the seismic data. Therefore, the seismic resolution is low and it is difficult to provide the information needed for thin layer prediction. In this paper, a spectral fitting method with horizon constraints is proposed. This method fully takes into account the spectral characteristics and tectonic changes of the seismic data. It can effectively extend the seismic frequency bandwidth by spectral fitting and improve the seismic resolution. At the same time, the structural information is integrated into the high-resolution processing as the layer information is used to constrain the target equation, and more accurate spectral features of multi-channel data can be obtained. Then the spectral weighting coefficient can be calculated more accurately, resulting in more realistic and accurate seismic data. At the same time, the seismic phase is not destroyed by the processing, so the structural features become clearer, especially for small fractures and thin layers. This method is used for comparison with traditional robust deconvolution and statistical wavelet deconvolution. The spectral components are more faithful and the resolution is higher when processed with this method.