检索结果-南通市图书馆

A hybrid WUDT-NAFnet for simultaneous source data deblending

Petroleum Science 2024年第3期21卷 1649-1659页

作者： Chao-Fan Ke Shao-Huan Zu Jun-Xing Cao Xu-Dong Jiang Chao Li Xing-Ye Liu Key Laboratory of Earth Exploration and Information Technology of Ministry of Education Chengdu University of Technology State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Chengdu University of Technology College of Geophysics Chengdu University of Technology

Simultaneous source technology,which reduces seismic survey time and improves the quality of seismic data by firing more than one source with a narrow time interval,is compromised by the massive blended ***,deblending algorithms have been developed to separate this ***,deep learning(DL)has been proved its great potential in suppressing the *** most popular DL method employs neural network as a filter to attenuate the blended noise in an iterative estimation and subtraction framework(IESF).However,there are still amplitude distortion and blended noise residual problems,especially when dealing with weak signal submerged in strong *** address these problems,we propose a hybrid WUDT-NAFnet,which contains two *** first network is a wavelet based U-shape deblending transformer network(WUDTnet),incorporated into IESF as a robust regularization term to iteratively separate the blended *** second network is a nonlinear activate free network(NAFnet)designed to recover the event amplitude and further suppress the weak noise residual in *** the hybrid network,the blended noise can be separated purposefully and *** using synthetic and field seismic data demonstrate that the WUDTNAFnet outperforms traditional curvelet transform(CT)based method and the deblending transformer(DT)model in terms of ***,for field applications,the data augmentation method of bicubic interpolation is applied to mitigate the feature difference between synthetic and field ***,the trained network exhibits strong signal preservation ability in numerical field example without requiring additional training.

关键词： Simultaneous-source deblending Deep learning Transformer

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

deblending by modified dictionary learning using Sparse Parameter Training

引用

Global Geology 2021年第4期24卷 226-238页

作者： Evinemi E Isaac MAO Weijian CHENG Shijun Research Center for Computational and Exploration Geophysics State Key Laboratory of Geodesy and Earth's DynamicsInnovation Academy for Precision Measurement Science and TechnologyCASWuhan 430077China University of Chinese Academy of Sciences Beijing 100049China

Considerable attempts have been made on removing the crosstalk noise in a simultaneous source data using the popular K-means Singular Value Decomposition algorithm(KSVD).Several hybrids of this method have been designed and successfully deployed,but the complex nature of blending noise makes it difficult to manipulate *** of the challenges of the K-means Singular Value Decomposition approach is the challenge to obtain an exact KSVD for each data patch which is believed to result in a better *** this work,we propose a learnable architecture capable of data training while retaining the K-means Singular Value Decomposition essence to deblend simultaneous source data.

关键词： deblending simultaneous-source sparse approximation dictionary learning deep learning

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Separation of inhomogeneous blended seismic data

引用

Applied Geophysics 2015年第3期12卷 327-333,466页

作者：刘强韩立国陈竞一陈雪张显娜吉林大学地球探测科学与技术学院长春130026 塔尔萨大学工程与自然科学学院奥克拉荷马74104

The frequencies of sources involved m conventional blended acquisition are the same. Each source transmits the full frequency band, and in general, significant effort is required to successfully produce and operate wideband sources. To solve this problem, inhomogeneous blended or decentralized blended acquisition is used, in which the dominant frequency and bandwidth of the source units in a blended array are not equal. When the inhomogeneous and conventional blending acquisitions adopt the same geometry and separation methods, the former has low signal-to-blending noise ratio. Therefore, we present a new separation method for such blended acquisition based on the synchrosqueezed wavelet transform. The proposed method offers better separation quality and decreases the computation time to approximately 1/3.

关键词： Inhomogeneous blended acquisition, synchrosqueezed wavelet transform deblending

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：