Imaging near-surface heterogeneities by natural migration of backscattered surface waves: Field data test
KAUST DepartmentCenter for Subsurface Imaging and Fluid Modeling
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division
Online Publication Date2017-03-06
Print Publication Date2017-05
Permanent link to this recordhttp://hdl.handle.net/10754/622980
MetadataShow full item record
AbstractWe have developed a methodology for detecting the presence of near-surface heterogeneities by naturally migrating backscattered surface waves in controlled-source data. The near-surface heterogeneities must be located within a depth of approximately one-third the dominant wavelength λ of the strong surface-wave arrivals. This natural migration method does not require knowledge of the near-surface phase-velocity distribution because it uses the recorded data to approximate the Green’s functions for migration. Prior to migration, the backscattered data are separated from the original records, and the band-passed filtered data are migrated to give an estimate of the migration image at a depth of approximately one-third λ. Each band-passed data set gives a migration image at a different depth. Results with synthetic data and field data recorded over known faults validate the effectiveness of this method. Migrating the surface waves in recorded 2D and 3D data sets accurately reveals the locations of known faults. The limitation of this method is that it requires a dense array of receivers with a geophone interval less than approximately one-half λ.
CitationLiu Z, AlTheyab A, Hanafy SM, Schuster G (2017) Imaging near-surface heterogeneities by natural migration of backscattered surface waves: Field data test. GEOPHYSICS 82: S197–S205. Available: http://dx.doi.org/10.1190/geo2016-0253.1.
SponsorsThe research reported in this paper was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We thank the sponsors of the Center for Subsurface Imaging and Fluid Modeling (CSIM) consortium for their support. We would also like to thank the high-performance computing center of KAUST for providing access to supercomputing facilities. We thank B. Guo and Z. Feng for editing the paper. A. AlTheyab thanks Saudi Aramco for sponsoring his graduate studies. We also thank the associate editor J. van der Neut and three anonymous reviewers whose reviews improved the quality of this manuscript.
PublisherSociety of Exploration Geophysicists