Study On Seismic Traveltime Inversion Based On Wavelet Analysis

Seismic exploration technology will be of great significance in the fields of energy exploration and marine geophysical prospecting in the future.In seismic exploration technology,the application of underground detection methods based on traveltime is also very common.The accuracy of traveltime information seriously affects the reliability of later inversion results,so how to pick up accurate traveltime information is extremely important.This article focuses on the problem that the data collected during seismic inversion often contains interference information that makes it difficult to interpret traveltime data.The main tasks are as follows:(1)This paper proposes a seismic traveltime inversion imaging method based on wavelet analysis.An improved wavelet threshold denoising algorithm is applied to seismic traveltime inversion,which improves the accuracy of traveltime data and makes the inversion results more objective and more reliable.The algorithm is mainly improved in two aspects.One is the selection of the threshold,and the other is the threshold quantization processing method.In the algorithm.We use the GCV(Generalized Cross-validation)threshold selection function to obtain the threshold.The specific method is to use the artificial bee colony algorithm to continuously iteratively optimize the function,and calculate the optimal threshold that is realistic.This algorithm can avoid the estimation of noise variance and improve the final denoising performance.In threshold quantization,an improved soft-hard threshold improved compromise method is used to improve the fidelity of the reconstructed signal.Combining the above two points can effectively suppress the noise in the spatiotemporal data,and help us pick up the traveltime information.These can improve the accuracy of the traveltime data,and then obtain a more objective and clear inversion result image.(2)This paper studies the seismic traveltime inversion imaging method at different frequencies.For the initial model,we choose to use appropriate different frequencies for forward calculation.We then pick up the traveltime information of the data at different frequencies after denoising and before denoising separately,and finally obtain the result image by iterative inversion,and analyze the effect of different frequencies on the inversion quality.In this paper,the forward modeling of seismic data is obtained by the wave-equation finite difference method,and then the improved algorithm and the selected contrast algorithms are used to process the noisy seismic data.From the perspective of different noise addition methods,the results of various stages of the seismic traveltime inversion imaging have verified that the proposed algorithm in this paper has a significantly better effect in seismic traveltime inversion than other algorithms.