A Time-Domain Seismic Imaging Method With Sparse Pulsed-Beams Data

被引:1
|
作者
Tuvi, Ram [1 ]
Zhao, Zeyu [1 ]
Sen, Mrinal K. [1 ]
机构
[1] Univ Texas Austin, John A & Katherine G Jackson Sch Geosci, Inst Geophys, Austin, TX 78758 USA
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2022年 / 60卷
关键词
Lead; Lattices; Transforms; Time-domain analysis; Time-frequency analysis; Surface waves; Surface treatment; Inverse theory; wave propagation; wavelet transform; PERFECTLY CONDUCTING WEDGE; WEAKLY INHOMOGENEOUS-MEDIA; LOCAL SPECTRAL-ANALYSIS; COMPLEX-SOURCE; SUMMATION FORMULATION; RADON-TRANSFORM; GAUSSIAN-BEAM; PART II; DEPENDENT RADIATION; EXCITED SCATTERING;
D O I
10.1109/TGRS.2021.3131270
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
A novel time-domain (TD) migration method in inhomogeneous media is proposed. The formulation is based on the phase-space pulsed beam summation (PS-PBS) method. We use pulsed beams (PBs) to transform the acquired seismic data and backpropagate the PBs & x2019; data. The PBs & x2019; data are represented along a spatial, spectral, and temporal phase-space lattice. Under the Born approximation, the data are given as the local interaction between pairs of PBs and subsurface layers. This relation is denoted as a local Snell & x2019;s law reflection from a localized region over the subsurface. Due to the spectral & x2013;temporal PBs & x2019; localization properties, only a few temporal data points correspond to each imaging point. The PBs & x2019; data provide an <italic>a priori</italic> sparse skeleton as the basis for the migration problem, which reduces the number of calculations needed to form images.
引用
收藏
页数:11
相关论文
共 50 条
  • [31] Velocity-independent time-domain seismic imaging using local event slopes
    Fomel, Sergey
    GEOPHYSICS, 2007, 72 (03) : S139 - S147
  • [32] Time-domain flaw imaging system
    Medina, L
    REVISTA MEXICANA DE FISICA, 2005, 51 (02) : 176 - 185
  • [33] Terahertz time-domain spectroscopy imaging
    Zhang Zhen-Wei
    Cui Wei-Li
    Zhang Yang
    Zhang Cun-Lin
    JOURNAL OF INFRARED AND MILLIMETER WAVES, 2006, 25 (03) : 217 - 220
  • [34] TIME-DOMAIN MICROWAVE TARGET IMAGING
    YEUNG, WK
    EVANS, S
    IEE PROCEEDINGS-H MICROWAVES ANTENNAS AND PROPAGATION, 1985, 132 (06) : 345 - 350
  • [35] Magnified time-domain ghost imaging
    Ryczkowski, Piotr
    Barbier, Margaux
    Friberg, Ari T.
    Dudley, John M.
    Genty, Goery
    APL PHOTONICS, 2017, 2 (04)
  • [36] Sparse network equivalent based on time-domain fitting
    Boaventura, WDC
    Semlyen, A
    Iravani, AR
    Lopes, A
    IEEE TRANSACTIONS ON POWER DELIVERY, 2002, 17 (01) : 182 - 189
  • [37] Fast Simulation of Microwave Devices via a Data-Sparse and Explicit Finite-Element Time-Domain Method
    Wan, T.
    Du, L.
    Zhu, J.
    APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL, 2016, 31 (05): : 574 - 581
  • [38] Time-domain terahertz compressive imaging
    Zanotto, L.
    Piccoli, R.
    Dong, J.
    Caraffini, D.
    Morandotti, R.
    Razzari, L.
    OPTICS EXPRESS, 2020, 28 (03) : 3795 - 3802
  • [39] Monotonicity based imaging method for time-domain eddy current problems
    Su, Z.
    Ventre, S.
    Udpa, L.
    Tamburrino, A.
    INVERSE PROBLEMS, 2017, 33 (12)
  • [40] Automated Variability Selection in Time-domain Imaging Surveys using Sparse Representations with Learned Dictionaries
    Moody, Daniela I.
    Wozniak, Przemek R.
    Brumby, Steven P.
    2015 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP (AIPR), 2015,