摘要
地震数据中的随机噪声毫无规律,常规去噪方法难以达到理想的效果,影响后续的地震数据解释和分析。为此,提出一种基于扩散模型的地震信号去噪方法。该方法的前向扩散过程是通过对地震数据进行一定程度的加噪,将地震数据变成存在大量各向同性的高斯噪声的含噪地震数据,再利用训练后的扩散模型对含噪数据进行重建,提高地震数据的信噪比。预测网络部分是基于改进的U-Net网络,该网络中引入了注意力模块和ResNet模块,以提高网络对重要区域的关注度,避免深度网络中的梯度消失问题。理论数据和实际数据的应用结果均验证了文中方法的有效性。该方法去噪效果远超FX滤波、SVD等传统去噪方法,同时也比经典的深度学习网络CNN、GAN更加优秀,能够完整地保留有效信号,极大提升地震数据的质量。
As the random noise in seismic data is highly irregular,conventional denoising methods often fail to achieve satisfactory results,thereby hindering subsequent interpretation and analysis of seismic data.Therefor,a seismic signal denoising method based on the diffusion model is proposed.The forward diffusion process of this method involves adding a certain degree of noise to the seismic data,transforming it into noisy seismic data with a large amount of isotropic Gaussian noise.Then,the trained diffusion model is usedtoreconstruct the noisy data and improve its signal-to-noise ratio.The prediction network component is an improved U-Net network,which incorporates attention modules and ResNet modules.These modules elevate the network’s attention on important regions and mitigate gradient disappearance in deep networks.Both theoretical and practical data have verified the effectiveness of the proposed method.In terms of denoising effect,it significantly surpasses traditional denoising methods such as FX filtering and SVD,and it also outperforms classic deep lear-ning networks like CNN and GAN.This approach effectively preserves valid signals,thereby significantly enhancing seismic dataquality.
作者
吴迪
文武
门哲
马一凡
WU Di;WEN Wu;MEN Zhe;MA Yifan(School of Geophysics,Chengdu University of Technology,Chengdu,Sichuan 610059,China;Acquisition Technology Institute,BGP Inc.,CNPC,Zhuozhou,Hebei 072751,China;School of Computer Science,Chengdu University of Information Technology,Chengdu,Sichuan 610225,China)
出处
《石油地球物理勘探》
EI
CSCD
北大核心
2024年第6期1252-1259,共8页
Oil Geophysical Prospecting
基金
中国石油天然气股份有限公司重大科技项目“羌塘盆地油气地质综合研究与勘探关键技术攻关”之课题“羌塘盆地高原地球物理勘探技术攻关”(2021DJ0804)
中国石油集团东方地球物理勘探有限责任公司重大科技专项“物探智能化关键技术研究”之课题“地震采集关键技术及装备智能化研发”(01-04-01-2024)联合资助。
关键词
随机噪声压制
扩散模型
残差模块
注意力模块
random noise suppression
diffusion model
residual module
attentionmodule
