Multisynchrosqueezing Generalized S-Transform and Its Application in Tight Sandstone Gas Reservoir Identification

被引:21
作者
Chen, Xuping [1 ,2 ]
Chen, Hui [1 ,2 ]
Li, Rui [2 ,3 ]
Hu, Ying [2 ,3 ]
Fang, Yuxia [2 ,3 ]
机构
[1] Chengdu Univ Technol, State Key Lab Oil & Gas Reservoir Geol & Explorat, Chengdu 610059, Peoples R China
[2] Chengdu Univ Technol, Geomath Key Lab Sichuan Prov, Chengdu 610059, Peoples R China
[3] Chengdu Univ Technol, Coll Informat Sci & Technol, Chengdu 610059, Peoples R China
基金
中国国家自然科学基金;
关键词
Reservoirs; Transforms; Estimation; Time-frequency analysis; Noise measurement; Geology; Continuous wavelet transforms; Instantaneous frequency (IF); multisynchrosqueezing generalized S-transform (GST); synchrosqueezing transform (SST); tight sandstone gas reservoirs; time-frequency (TF) analysis (TFA); TIME-FREQUENCY; SYNCHROSQUEEZING TRANSFORM; ATTENUATION;
D O I
10.1109/LGRS.2020.3043047
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Synchrosqueezing transform (SST) is a high-resolution time-frequency (TF) analysis (TFA) approach for seismic spectral anomaly detection. Here, a novel method called multisynchrosqueezing generalized S-transform (GST) is proposed and applied for the identification of tight sandstone gas reservoirs. In this method, a signal model named the Gaussian-Modulated Signal Model (GMSM) is introduced to estimate the instantaneous frequency (IF) of the signal in the GST's spectrum. Then, an iterative algorithm constantly approximating IF is constructed to provide a highly energy-concentrated TF representation while allowing for signal reconstruction. Compared to some advanced TFA methods, the proposed method has better energy-concentrated performance due to an accurate estimate of the IF. A simulated signal and field data are employed to verify the effectiveness of the proposed method. It is concluded that the proposed method has great potential as a TFA technique for identifying tight sandstone gas reservoirs.
引用
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页数:5
相关论文
共 27 条
  • [21] Synchrosqueezing Matching Pursuit Time-Frequency Analysis
    Xu, Lu
    Yin, Xingyao
    Zong, Zhaoyun
    Li, Kun
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2021, 18 (03) : 411 - 415
  • [22] Detection of gas and water using HHT by analyzing P- and S-wave attenuation in tight sandstone gas reservoirs
    Xue, Ya-juan
    Cao, Jun-xing
    Wang, Da-xing
    Tian, Ren-fei
    Shu, Ya-xiang
    [J]. JOURNAL OF APPLIED GEOPHYSICS, 2013, 98 : 134 - 143
  • [23] Multisynchrosqueezing Transform
    Yu, Gang
    Wang, Zhonghua
    Zhao, Ping
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 66 (07) : 5441 - 5455
  • [24] Yu G, 2018, CHIN AUTOM CONGR, P3468, DOI 10.1109/CAC.2018.8623521
  • [25] Local maximum synchrosqueezing transform: An energy-concentrated time-frequency analysis tool
    Yu, Gang
    Wang, Zhonghua
    Zhao, Ping
    Li, Zhen
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 117 : 537 - 552
  • [26] Multiple squeezes from adaptive chirplet transform
    Zhu, Xiangxiang
    Zhang, Zhuosheng
    Li, Zhen
    Gao, Jinghuai
    Huang, Xin
    Wen, Guangrui
    [J]. SIGNAL PROCESSING, 2019, 163 : 26 - 40
  • [27] Tight gas sandstone reservoirs in China: characteristics and recognition criteria
    Zou, Caineng
    Zhu, Rukai
    Liu, Keyu
    Su, Ling
    Bai, Bin
    Zhang, Xiangxiang
    Yuan, Xuejian
    Wang, Jinhong
    [J]. JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2012, 88-89 : 82 - 91