基于滤波处理的地震散射波分离方法研究综述

Review of Research on Filtering-based Methods for Seismic Scattered Wave Separation

在地震勘探中,由于地下结构错综复杂,多尺度非均匀的地质体常会形成包含反射波、散射波等在内的复杂的地震波场。传统的成像方法一般只考虑反射波场,忽略了散射波场,这使得细小结构无法准确成像,从而影响对复杂构造的识别。为了对小尺度构造进行准确的地震成像,要将散射波从地震波场中分离出来。在众多波场分离算法中,基于滤波的波场分离方法可以准确提取散射波,提高成像分辨率。本文调研和归纳多种基于滤波处理的地震散射波分离方法,围绕国内外学者在滤波处理波场分离方面的研究成果,总结各种方法的研究进展,并对比和分析各方法的分离效果,最后结合人工智能深度学习的研究趋势,对未来滤波处理散射波分离的发展方向进行展望。

In seismic exploration,complex seismic wave fields comprising reflected waves,scattered waves,and other phenomena are formed due to the intricate nature of underground structures.Traditional imaging methods typically focus solely on the reflected wave field,disregarding the scattered wave field.This limitation hampers accurate imaging of small-scale structures and impedes the identification of complex structures.To address this challenge and achieve precise imaging of small-scale structures,it is crucial to separate from the scattered waves from the seismic wave field.Among the various wave field separation algorithms,filtering-based methods have shown promising results in accurately extracting scattered waves and enhancing imaging resolution.This study explores and summarizes different methods for seismic scattered wave separation based on filtering techniques.By reviewing the research findings of both domestic and international scholars in the field of filtering-based scattered wave separation,the study provides an overview of the progress made and compares and analyzes the separation effects of each method.Additionally,considering the advancements in deep learning within the realm of artificial intelligence,the future development direction of filtering-based scattered wave separation is also envisioned.