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基于多尺度窗口生成器网络的抽油机噪声压制

马一凡 文武 薛雅娟 文晓涛 徐虹

石油地球物理勘探2024,Vol.59Issue(4):684-691,8.
石油地球物理勘探2024,Vol.59Issue(4):684-691,8.DOI:10.13810/j.cnki.issn.1000-7210.2024.04.004

基于多尺度窗口生成器网络的抽油机噪声压制

Noise suppression of pumping unit based on multi-scale window generator network

马一凡 1文武 1薛雅娟 2文晓涛 3徐虹1

作者信息

  • 1. 成都信息工程大学计算机学院,四川成都 610225
  • 2. 成都信息工程大学通信工程学院,四川成都 610225
  • 3. 成都理工大学地球物理学院,四川成都 610225
  • 折叠

摘要

Abstract

The noise of the pumping unit strongly interferes with the exploration and development of old oil fields and seriously reduces the signal-to-noise ratio of seismic data.Therefore,a pumping unit noise suppres-sion method based on a multi-scale window generator network is proposed.The constructed network is mainly composed of a double-layer encoder-decoder structure,and accurate denoising results can be obtained by com-bining characteristic information of different layers.The utilization of different-sized windows in different layers for feature extraction can effectively expand the sensing range of the neural network and extract more useful fea-tures from the pumping unit noise.To prevent the degradation of the network,residual connections are used re-spectively in each block of the encoder and decoder.The residual block of the encoder adopts the anti-bottle-neck design with a large amount of convolution kernels in the middle and small at both ends to extract more fea-tures of seismic data.The decoder uses one-fifth of the convolutional layers of the encoder,speeding up model training and seismic data reconstruction.The network constructed in this way can effectively suppress pumping unit noise in seismic data by using multi-scale semantic information.Both simulated data and real data experi-mental results show that compared with DnCNN,GAN,and MLGNet,the proposed method can obtain high-quality denoising results and retain valid data to the greatest extent.

关键词

地震资料/噪声压制/多尺度窗口/生成器/信噪比

Key words

seismic data/noise suppression/multi-scale window/generator/signal-to-noise ratio

分类

天文与地球科学

引用本文复制引用

马一凡,文武,薛雅娟,文晓涛,徐虹..基于多尺度窗口生成器网络的抽油机噪声压制[J].石油地球物理勘探,2024,59(4):684-691,8.

基金项目

本项研究受四川省中央引导地方科技发展专项"岩石物理驱动的非常规油气地震多参数预测理论与方法研究"(2023ZYD0158)和四川省自然科学基金项目"四川盆地碳酸盐岩储层的脉冲神经网络识别理论及方法研究"(2023NSFSC0258)联合资助. (2023ZYD0158)

石油地球物理勘探

OA北大核心CSTPCD

1000-7210

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