Hybrid regularization methods for seismic reflectivity inversion

被引：10
|
作者：
Wang Y. [1 ]
Cui Y. [2 ]
Yang C. [1 ]
机构：
[1] Key Laboratory of Petroleum Resources Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029
[2] Geoscience Research Institute of Shengli Oilfield, SINOPEC
来源：
GEM - International Journal on Geomathematics | 2011年 / 2卷 / 1期
基金：
中国国家自然科学基金;
关键词：
Computational seismology; Image processing; Numerical approximations; Numerical solutions; Regularization;
D O I：
10.1007/s13137-011-0014-1
中图分类号：
学科分类号：
摘要：
In this paper, we consider new solution methods for seismic deconvolution problem in seismic data processing. We study regularization methods and introduce a hybrid regularization scheme for seismic deconvolution. Fast gradient descent methods are considered for solving the hybrid regularization model. An l1 minimization model based on primal-dual interior point methods is presented and used for comparison. Numerical experiments for synthetic signal simulations and field data applications are given. The results show the potentials for applications of the developed method. © 2011 Springer-Verlag.
引用
收藏
页码：87 / 112
页数：25
相关论文
共 50 条
  • [1] A Hybrid Regularization Operator and Its Application in Seismic Inversion
    Liu, Yangting
    Liu, Chenguang
    Xie, Chengliang
    Zhao, Qing-Xian
    [J]. IEEE ACCESS, 2021, 9 : 117378 - 117387
  • [2] On iterative regularization methods for migration deconvolution and inversion in seismic imaging
    Wang Yan-Fei
    Yang Chang-Chun
    Duan Qiu-Liang
    [J]. CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2009, 52 (06): : 1615 - 1624
  • [3] Multichannel algorithms for seismic reflectivity inversion
    Wang, Ruo
    Wang, Yanghua
    [J]. JOURNAL OF GEOPHYSICS AND ENGINEERING, 2017, 14 (01) : 41 - 50
  • [4] Choice of regularization weight in basis pursuit reflectivity inversion
    Sen, Mrinal K.
    Biswas, Reetam
    [J]. JOURNAL OF GEOPHYSICS AND ENGINEERING, 2015, 12 (01) : 70 - 79
  • [5] Sparse reflectivity inversion for nonstationary seismic data
    Chai, Xintao
    Wang, Shangxu
    Yuan, Sanyi
    Zhao, Jianguo
    Sun, Langqiu
    Wei, Xian
    [J]. GEOPHYSICS, 2014, 79 (03) : V93 - V105
  • [6] Optimal Seismic Reflectivity Inversion: Data-Driven lp -Loss-lq -Regularization Sparse Regression
    Li, Fangyu
    Xie, Rui
    Song, Wen-Zhan
    Chen, Hui
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2019, 16 (05) : 806 - 810
  • [7] THE DUAL REGULARIZATION APPROACH TO SEISMIC VELOCITY INVERSION
    GOCKENBACH, MS
    SYMES, WW
    TAPIA, RA
    [J]. INVERSE PROBLEMS, 1995, 11 (03) : 501 - 531
  • [8] GII regularization technique for seismic data inversion
    Menezes de Souza, Raphael Vieira
    Peters, Franciane Conceicao
    Mansur, Webe Joao
    Salles, Halina dos Santos
    Torres Bautista, Kristian David
    Santos, Luiz Alberto
    [J]. JOURNAL OF APPLIED GEOPHYSICS, 2019, 160 : 229 - 235
  • [9] Seismic Inversion Methods
    Jackiewicz, Jason
    [J]. STELLAR PULSATION: CHALLENGES FOR THEORY AND OBSERVATION, 2009, 1170 : 574 - 576
  • [10] ESTIMATING THE ENERGY-SOURCE AND REFLECTIVITY BY SEISMIC INVERSION
    MINKOFF, SE
    SYMES, WW
    [J]. INVERSE PROBLEMS, 1995, 11 (02) : 383 - 395
12345