1. Radon domain interferometric interpolation of sparse seismic data
- Author
-
Jie Shao, Yibo Wang, and Xu Chang
- Subjects
Data processing ,010504 meteorology & atmospheric sciences ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,chemistry.chemical_element ,Radon ,010502 geochemistry & geophysics ,01 natural sciences ,Physics::Geophysics ,Domain (software engineering) ,Interferometry ,Geophysics ,Data acquisition ,chemistry ,Geochemistry and Petrology ,Geology ,Multiple ,0105 earth and related environmental sciences ,Remote sensing ,Interpolation - Abstract
The interpolation of sparse seismic data is important for seismic data processing, especially in the case of marine data acquisition. The conventional interferometric interpolation method interpolates missing data based on seismic interferometry in the time-space domain. However, missing traces and the limited acquisition aperture will reduce the quality and accuracy of virtual shot gathers, thereby affecting the final interpolation results. To improve the conventional method, we have adopted a four-step Radon domain interferometric interpolation method for sparse seismic data. First, we generate synthetic seismic data with a water-layer model and replace missing traces in the input data with synthetic traces. Second, we sort the input shot gathers into common-receiver-point (CRP) gathers and transform the CRP gathers into the Radon domain using a sparse Radon transform method. Third, we perform Radon domain seismic interferometric interpolation by cross-correlating traces with the same ray parameter and summing over all different ray parameters to obtain a virtual shot gather. Fourth, we apply a 1D least-squares matching filter to the virtual shot gather to obtain the interpolation result. Numerical and field examples demonstrate that our method can effectively interpolate sparse seismic data. Compared with the conventional time-space domain interferometric interpolation method, our method can provide more accurate interpolation results. Moreover, it is less sensitive to the depth of the water layer and an inaccurate impedance contrast of the water bottom.
- Published
- 2021