4.6 Article

Multicomponent georadar data: Some important implications for data acquisition and processing

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GEOPHYSICS
卷 65, 期 5, 页码 1542-1552

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SOC EXPLORATION GEOPHYSICISTS
DOI: 10.1190/1.1444842

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Many seismic reflection processing techniques are applied routinely to ground-penetrating radar (georadar or GPR) data Although similarities exist between seismic (acoustic) and radar wave propagation there are some significant differences some of the most important of which an associated with the dipole nature (1) of georadar sources and receivers and (2) of elemental sources used to represent scattering bodies. Neglecting the dipole character of electromagnetic surveys may result in incomplete or biased images of the subsurface. In an attempt to understand better the consequences of recording dipolar wavefields, we have simulated numerous multicomponent georadar data sets. These simulations an based on the weak scattering (Born) approximation, such that point heterogeneities in the subsurface can be represented by infinitesimal dipoles with moments parallel and proportional to the incident georadar wavefields. The effects of depolarization and dispersion are not included. Nevertheless, many subsurface structures can be modeled by suites of appropriately distributed infinitesimal dipoles. Georadar images of even the simplest subsurface structures are shown to depend strongly on the relative orientations and positions of the source and receiver antennas. A positive aspect of dipolar wavefields is that multicomponent georadar profiles contain information on the locations of both in-plane and out-of-plane structures. Furthermore, pseudoscalar wavefields can be simulated from coincident georadar data sets acquired with two pairs of parallel source-receiver antennas one oriented perpendicular to the other. Pseudoscalar georadar data, which are characterized by low degrees of directionality, can be processed (including migration) confidently using standard seismic processing software (assuming that dispersion is not a major problem). To illustrate the advantages of multicomponent georadar data, two field examples are presented. One demonstrates the value of recording dual-component georadar data along isolated profiles; the other shows the benefits of combining 3-D georadar data sets acquired with dual component source-receiver antenna pairs to form pseudoscalar wavefield images.

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