KAUST DepartmentPhysical Sciences and Engineering (PSE) Division
Earth Science and Engineering Program
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AbstractWe present the theory for near-field superresolution imaging with surface waves and time reverse mirrors (TRMs). Theoretical formulas and numerical results show that applying the TRM operation to surface waves in an elastic half-space can achieve superresolution imaging of subwavelength scatterers if they are located less than about 1/2 of the shear wavelength from the source line. We also show that the TRM operation for a single frequency is equivalent to natural migration, which uses the recorded data to approximate the Green’s functions for migration, and only costs O(N4) algebraic operations for poststack migration compared to O(N6) operations for natural prestack migration. Here, we assume the sources and receivers are on an N × N grid and there are N2 trial image points on the free surface. Our theoretical predictions of superresolution are validated with tests on synthetic data. The field-data tests suggest that hidden faults at the near surface can be detected with subwavelength imaging of surface waves by using the TRM operation if they are no deeper than about 1/2 the dominant shear wavelength.
CitationFu L, Liu Z, Schuster G (2017) Superresolution Near-field Imaging with Surface Waves. Geophysical Journal International. Available: http://dx.doi.org/10.1093/gji/ggx466.
SponsorsThe research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia. We are grateful to the sponsors of the Center for Subsurface Imaging and Modeling (CSIM) Consortium for their financial support. For computer time, this research used the resources of the Supercomputing Laboratory at KAUST and the IT Research Computing Group. We thank them for providing the computational resources required for carrying out this work. We greatly appreciate the constructive comments and suggestions from editor Herve Chauris, and two anonymous reviewers, which helped improve this paper.
PublisherOxford University Press (OUP)