Interpolation Algorithm Based On The Recorded Seismic Trace Gather

Shallow seismic exploration attracted great attention from the engineering as it can provide the parameters of Elastodynamics in the engineering investigation. As the impact of the shallow geological conditions and the environment of construction, insufficient space sampling often exists in the shallow seismic records, which is not conducive to the subsequent signal processing and detailed interpretation, so seismic trace interpolation is being used widely to solve this problem.The existing seismic trace interpolation mostly follow the processing mode of deep oil and gas seismic exploration, which doesn't take into amount of the complexity of shallow seismic records. The affects of shallow geological structure to the shallow seismic signal is much stronger than the deep, and shallow seismic records are affected by the direct wave, surface wave, human noise, industrial noise, surface relief, and many other factors. So the shallow seismic records are much more complex than the deep records, and the research of interpolation algorithm which is fit for the shallow seismic records has great practical significance.The image processing is widely used in the digital image processing of Geophysics, but until now, it has not been applied to the seismic trace interpolation. This article uses image interpolation into the trace interpolation of shallow seismic base on the specificity of shallow seismic records, which doesn't have the whole (multi-channel) regularity but with strong correlation between the adjacent channels, and makes use of the image interpolation can fully consider the proximity of the relevant characteristics of sampling points. Through the sampling rate conversion and directional interpolation algorithm, this manner can be used well in shallow seismic data interpolation.The BP artificial neural network has strong capacity of generalization, and it can simulate the complex function. So, in this paper, this characteristic is used in simulating the complex internal relationship among the channels of shallow seismic records, with using the original seismic records as learning samples. Then use the mature network in trace interpolation of the shallow seismic data with alias. This interpolation algorithm can achieve good results.The results of trace interpolation used in analog and practical shallow seismic records indicate that the directional interpolation algorithm and the interpolation algorithm based on the BP artificial neural network have good practicability.