北京大学学报（自然科学版）2024，Vol.60Issue(3)：453-463,11.DOI:10.13209/j.0479-8023.2024.031
基于无监督神经网络匹配算法的叠前表面多次波压制方法
Prestack Surface Multiple Suppression Method Based on Matching Algorithm with Unsupervised Neural Network
摘要
Abstract
To effectively suppress surface multiples in marine seismic data and then correctly image the exploration target,a prestack surface multiple attenuation algorithm based on unsupervised neural networks is proposed,which combines neural network methods with surface-related multiple elimination(SRME)methods.By continuously decreasing the learning rate,the unsupervised neural network replaces the matching filter operator for suppressing surface multiples in the prestack seismic data.This method requires neither traditional matching algorithms nor training on labeled datasets.The application of simple synthetic data,Sigsbee model data and field data verifies the effectiveness of the proposed method for surface multiple wave suppression.关键词
无监督神经网络/表面多次波压制/叠前地震数据/匹配算法Key words
unsupervised neural networks/surface multiple suppression/prestack seismic data/matching algorithm引用本文复制引用
刘立超,胡天跃,李徯徯,刘依谋,梁上林,黄建东..基于无监督神经网络匹配算法的叠前表面多次波压制方法[J].北京大学学报（自然科学版）,2024,60(3):453-463,11.基金项目
国家自然科学基金(42274163)、国家重点研发计划(2018YFA0702503)和中国石油天然气集团有限公司-北京大学基础研究项目资助 （42274163）
