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    Least-squares migration of multisource data with a deblurring filter

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    Type
    Article
    Authors
    Dai, Wei
    Wang, Xin
    Schuster, Gerard T. cc
    KAUST Department
    Center for Subsurface Imaging and Fluid Modeling
    Earth Science and Engineering Program
    Environmental Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2011-09
    Permanent link to this record
    http://hdl.handle.net/10754/561868
    
    Metadata
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    Abstract
    Least-squares migration (LSM) has been shown to be able to produce high-quality migration images, but its computational cost is considered to be too high for practical imaging. We have developed a multisource least-squares migration algorithm (MLSM) to increase the computational efficiency by using the blended sources processing technique. To expedite convergence, a multisource deblurring filter is used as a preconditioner to reduce the data residual. This MLSM algorithm is applicable with Kirchhoff migration, wave-equation migration, or reverse time migration, and the gain in computational efficiency depends on the choice of migration method. Numerical results with Kirchhoff LSM on the 2D SEG/EAGE salt model show that an accurate image is obtained by migrating a supergather of 320 phase-encoded shots. When the encoding functions are the same for every iteration, the input/output cost of MLSM is reduced by 320 times. Empirical results show that the crosstalk noise introduced by blended sources is more effectively reduced when the encoding functions are changed at every iteration. The analysis of signal-to-noise ratio (S/N) suggests that not too many iterations are needed to enhance the S/N to an acceptable level. Therefore, when implemented with wave-equation migration or reverse time migration methods, the MLSM algorithm can be more efficient than the conventional migration method. © 2011 Society of Exploration Geophysicists.
    Citation
    Dai, W., Wang, X., & Schuster, G. T. (2011). Least-squares migration of multisource data with a deblurring filter. GEOPHYSICS, 76(5), R135–R146. doi:10.1190/geo2010-0159.1
    Sponsors
    We are grateful to King Abdullah University of Science and Technology and the sponsors of the 2009 University of Utah Tomography and Modeling/Migration (UTAM) Consortium for their financial support. We also thank the associate editor and three anonymous reviewers for their constructive comments.
    Publisher
    Society of Exploration Geophysicists
    Journal
    Geophysics
    DOI
    10.1190/geo2010-0159.1
    ae974a485f413a2113503eed53cd6c53
    10.1190/geo2010-0159.1
    Scopus Count
    Collections
    Articles; Environmental Science and Engineering Program; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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