| As the detection object becomes more and more complex,the reverse time migration(RTM)adapted to the undulating interface and complex structure has been continuously developed.This imaging method can reconstruct the material morphology of the unobservable area with high precision.However,this algorithm has low computational efficiency and low wavenumber atifact,which reduces its practicality.Therefore,This thesis focuses on these two issues.To solve the problem of low computational efficiency of the RTM,This thesis simulates and compares the received waveforms of the finite difference time domain(FDTD)method and the pseudospectral time-domain(PSTD)method,indicating that the former requires numerical stability to dissect at least 12 grid densities within a wavelength,while the latter requires only 2 grids.It shows that the PSTD can be divided into large grids,thereby reducing the space storage and calculation amount,and the calculation efficiency is greatly improved;In addition,under the respective accuracy requirements of the above two algorithms,the maximum relative error between the received waveforms is calculated to be 1.13%,and the average error is 0.61%,so it is effective to use PSTD instead of FDTD for numerical simulation method.Aiming at the problem of electromagnetic wave propagation attenuation in high-conductivity media,This thesis applies the attenuation compensated method that changes the sign of conductivity to RTM to ensure the symmetry of the wave equation when the electromagnetic wave propagates in reverse time.The simulation waveform shows that the attenuation compensated RTM can restore the signal attenuation caused by the conductivity well,thereby improving the imaging resolution.In view of the phenomenon of low-frequency noise in the imaging of the RTM,starting from the mechanism of noise generation,This thesis first analyzes the RTM based on the time window cross-correlation imaging conditions.The comparison with the traditional cross-correlation imaging results shows the algorithm has better denoising effect and then the wave-field decomposition method is applied from the denoising during the propagation process and the Laplace filter method is applied from the post-imaging filtering,and the two denoising methods are combined.The comparison of the simulation results shows that the wave-field decomposition combined with the Laplace filter is the best denoising method.Finally,This thesis applies the RTM of improved to tunnel disease detection imaging.By imaging three types of tunnel disease structures,it is observed that this algorithm can clearly image tunnel disease structures,indicating that the RTM of improved can provide theoretical support for tunnel disease imaging research. |
