Oil Geophysical Prospecting 2022 Seismic impedance inversion method based on temporal convolutional neural network

被引：0
|
作者：
Wang Z. [1 ]
Xu H. [1 ]
Yang M. [1 ]
Zhao Y. [1 ]
机构：
[1] College of Geophysics and Petroleum Resources, Yangtze University, Wuhan
来源：
Shiyou Diqiu Wuli Kantan/Oil Geophysical Prospecting | 2022年 / 57卷 / 02期
关键词：
Inversion mapping model; Reservoir prediction; Seismic impedance inversion; Temporal convolutional neural networks;
D O I：
10.13810/j.cnki.issn.1000-7210.2022.02.004
中图分类号：
学科分类号：
摘要：
Seismic impedance inversion is an important method for reservoir prediction. The accuracy of linear seismic impedance inversion methods depends on the quality of the initial geological model. To get a high-accuracy solution, one can adopt a completely nonlinear method. In view of this, a temporal convolutional neural network (TCN) is first constructed by using a fully convolutional neural network, dilated convolution, causal convolution and a residual block. On this basis, a nonlinear mapping relationship is established between seismic data and wave impedance. Then, samples are trained by the network to yield an inverse mapping model. Further, seismic impedance is obtained by inputting seismic data into the model. According to the test results of forward data and actual data, the method realizes the mapping between seismic data and seismic impedance. It provides an intelligent method with parallel computing power and adaptive structure for seismic impedance inversion and has been applied in sandstone and mudstone reservoir prediction of Gang 2025 Block. © 2022, Editorial Department OIL GEOPHYSICAL PROSPECTING. All right reserved.
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页码：279 / 286and296
相关论文
共 26 条
  • [21] HE K M, ZHANG X Y, REN S Q, Et al., Deep residual learning for image recognition, 2016 IEEE Con-ference on Computer Vision and Pattern Recognition (CVPR), pp. 770-778, (2016)
  • [22] CHEN Guoda, Historistic-causationist geotectonics, Geotectonicaet Metallogenia, 16, 1, pp. 1-71, (1992)
  • [23] XIA Shan, A brief introduction to "history causality geotectonics, Geology in China, 28, 12, pp. 12-28, (1992)
  • [24] WU Zhangfan, HE Zhonghua, JIANG Wei, Et al., Characteristics of fault block-lithologic reservoir in third member of Shahejie formation in deep South-Banqiao sag of Dagang oilfield, Global Geology, 38, 1, pp. 184-193, (2019)
  • [25] GUO Jinfeng, LI Hongxiang, SU Junqing, Et al., Petroleum formation and accumulation in the third member of Shahejie formation in Binhai nose-shaped high structure, Natural Gas Geoscience, 21, 4, pp. 554-558, (2010)
  • [26] ZHENG Yabin, WANG Yanbin, DENG Baorong, Et al., Reservoir characteristic study of block Gang172, Special Oil & Gas Reservoirs, 14, 4, pp. 26-28, (2007)
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