石油物探2025，Vol.64Issue(4)：679-690,12.DOI:10.12431/issn.1000-1441.2024.0171
基于物理信息约束的智能化面波压制技术
Intelligent surface wave suppression technology based on physical information constraints
摘要
Abstract
Surface wave suppression directly influences the imaging quality and interpretation accuracy of seismic data.In view of the limited identification accuracy and generalization of intelligent noise suppression based on a completely data-driven deep learning architecture,a physically constrained surface wave suppression technique is proposed.To enhance noise recognition,a UNET architecture with dual-channel input,jointly from the time-space domain and corresponding frequency-wavenumber domain before denoising,is constructed to establish the mapping relationship between input data and output noise data in the time-space domain.Based on the characteristics of surface waves as regular noises,structural similarity regularization operators are introduced into the loss function to further enhance the network's ability to recognize noises.To address different physical characteristics of surface waves in different work areas,noise frequency and apparent velocity distributions are used as the constraints for further processing of output noise data to obtain higher-precision noise predictions,which will be subtracted from input data using an adaptive subtraction algorithm to obtain final denoised data.The testing on several field data sets shows superior denoising accuracy and generalization capability of the proposed algorithm.关键词
面波噪声压制/双域联合/UNET网络/结构约束/自适应相减Key words
surface wave suppression/dual-domain data input/UNET/structural similarity constraint/adaptive subtraction分类
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陶永慧..基于物理信息约束的智能化面波压制技术[J].石油物探,2025,64(4):679-690,12.基金项目
国家自然科学基金企业创新发展联合基金重大项目(U23B6010)资助.This research is financially supported by the Major Project of National Natural Science Foundation of China(Grant No.U23B6010). （U23B6010）
