Research On Least Square Reverse Time Migration Method

The quality of seismic migration imaging is critical for later seismic processing and reservoir mechanism interpretation.There are three main methods commonly used in seismic migration imaging.The first is the Kirchhoff migration based on the ray theory,the second is the one-way wave migration based on the one-way wave theory and the reverse-time migration based on the two-way wave theory.Among them,the reverse time migration based on the two-way wave theory can realize the migration imaging of the steep dip profile and solve the caustics problem of the multi-wave imaging.However,there are still low-frequency noise in the imaging results of reverse time migration,which will cover part of the effective structural information,and the imaging resolution of reverse time migration is limited.In deep imaging,there are defects such as amplitude imbalance and difficulty in effective energy identification.The least squares reverse time migration is based on the traditional reverse time migration imaging.Combined with the inversion idea,the seismic profile is offset and imaged,which can effectively suppress low frequency imaging noise and improve the resolution of deep reservoir imaging.This method has higher amplitude-preserving performance and higher accuracy.Moreover,it uses the offset problem as extrapolation of time rather than depth extrapolation to avoid dissipation of energy.The main idea of this paper is to realize the acoustic least squares reverse time migration based on the reverse time migration and the inversion idea.Firstly,the forward modeling of the two-dimensional acoustic wave equation is carried out,then the inverse time delay of the received wave field is performed,then the reverse time migration is realized by cross-correlation imaging,and finally the least squares reverse time migration is performed on the basis of the reverse time migration..The main research results of this paper are:(1)forward modeling of two-dimensional acoustic waves with PML boundary conditions;(2)two-dimensional acoustic wave reverse time migration with cross-correlation imaging conditions;(3)two-dimensional realization The acoustic least squares reverse time offset is applied.