Shallow Seismic Exploration Acquisition Design Based On Compressed Sensing Theory

Seismic acquisition is the most costly work in the process of seismic exploration,even accounting for more than 80% of the cost.Therefore,how to improve traditional seismic acquisition methods and reduce the cost of seismic acquisition is an important research branch of seismic exploration.In traditional seismic acquisition,geophones are regularly arranged on the ground according to Nyquist sampling theorem,so the cost is very high.The recently emerged compressed sensing theory can randomly arrange the geophones and obtain complete data that meets the sampling theorem through seismic data reconstruction.Compressed sensing theory can design new sampling methods,which can reduce field work time,improve the acquisition efficiency of seismic exploration,and reduce acquisition costs.It is of revolutionary significance for the development of seismic exploration.Based on the compressed sensing theory,the seismic data are collected while compressing in actual work.Using the sparse expression characteristics of seismic signals,the sampling rate is much lower than the traditional Nyquist sampling rate to reconstruct the complete seismic records,which can save the sampling cost and shorten the sampling period to a great extent.At present,compressed sensing theory is mainly used in petroleum seismic exploration in the field of geophysics,and the research in shallow seismic exploration has not yet begun.This study is based on the theory of compressed sensing to study the acquisition method of shallow seismic exploration,and its purpose is to study how to better collect data and obtain ideal reconstruction results.Compressed sensing requires random sampling.According to this requirement,scholars have proposed a variety of random sampling methods,such as Gaussian,Bernoulli,and so on.However,when sampling with these random sampling methods,it is easy to cause the sampling points to be too clustered or scattered.Reconstruction using these sampling points often fails to obtain a better reconstruction effect.In order to solve the above problems,the paper proposes a new sampling method-edge-maintaining segmented random sampling.This method can not only maintain edge sampling but also control the large sampling interval.It can be applied to seismic exploration acquisition to improve the acquisition efficient.Finally,a large number of numerical experiments and comparisons of reconstruction effects show that this data acquisition method has better reconstruction effects than random sampling and segmented random sampling,and the offset of the reconstructed data is closer to the offset result of the complete acquisition data;The simulated sampling of real data in shallow seismic exploration proves that compressed sensing theory can be applied to shallow seismic exploration.The sampling method proposed in this paper has important potential in shallow seismic exploration.