中国海洋大学学报（自然科学版）2024，Vol.54Issue(8)：123-131,9.DOI:10.16441/j.cnki.hdxb.20230136
基于UNet结构生成对抗网络的海底地震勘探数据混叠噪声压制方法
Ocean Bottom Seismic Based on Generation of Countermeasure Network of Unet Structure Data Aliasing Noise Suppression Method
摘要
Abstract
The authors of proposes an aliasing noise suppression method for seabed seismic data based on UNet structure generation Counteraction network(Pix2PixGAN).The neural network mainly con-structs a generator and discriminator suitable for aliasing noise suppression.The generator is an UNet structure,which can extract and integrate feature mapping information of data.By adding skip-connec-tion,more details can be preserved;The discriminator is composed of two convolutional modules.Through PatchGAN,multiple data volumes of fixed size are output and Dropout2d layer is added to optimize the training speed of the discriminator.More than four thousand data sets were made to train the network model,and the obtained training parameters were loaded into the test network.After the verification of the test data sets and compared with the conventional denoising methods,it is verified that the aliasing noise suppression method adopted in this paper has higher suppression accuracy and efficiency.关键词
生成对抗网络/海底地震勘探/地震数据/混叠/噪声压制Key words
generative adversarial network/ocean bottom seismic exploration/seismic data/aliasing noise/noise suppression分类
海洋科学引用本文复制引用
童思友,刘岗,徐秀刚,王忠成,王金刚,杨德宽..基于UNet结构生成对抗网络的海底地震勘探数据混叠噪声压制方法[J].中国海洋大学学报（自然科学版）,2024,54(8):123-131,9.基金项目
国家自然科学基金项目(42074140)资助 Supported by the National Natural Science Foundation of China(42074140) （42074140）
