Exploiting Lateral Resolution of Near-Surface Seismic Refraction Methods

来源 :Journal of Earth Science | 被引量 : 0次 | 上传用户:wwjms
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The 1D τ-p inversion algorithm is widely employed to generate starting models with most computer programs that implement refraction tomography. However, this algorithm emphasizes the vertical resolution of many layers, and as a result, it frequently fails to detect even large lateral variations in seismic velocities, such as the decreases that are indicative of shear zones. This study presents a case that demonstrates the failure of the 1D τ-p inversion algorithm to define or even detect a major shear zone that is 50 m or ten stations wide. Furthermore, the majority of refraction tomography programs parameterize the seismic velocities within each layer with vertical velocity gradients. By contrast, the 2D generalized reciprocal method (GRM) inversion algorithms emphasize the lateral resolution of individual layers. This study demonstrates the successful detection and definition of the 50-m wide shear zone with the GRM inversion algorithms. The existence of the shear zone is corroborated by a 2D analysis of the head wave amplitudes and by numerous closely spaced orthogonal seismic profiles carried out as part of a later 3D refraction investigation. Furthermore, a 1D analysis of the head wave amplitudes indicates that a reversal in the seismic velocities, rather than vertical velocity gradients, occurs in the weathered layers. While all seismic refraction operations should aim to provide as accurate depth estimates as is practical, the major conclusion reached in this study is that refraction inversion algorithms that emphasize the lateral resolution of individual layers generate more useful results for geotechnical and environmental applications. The advantages of the improved lateral resolution are obtained with 2D profiles in which the structural features can be recognized from the magnitudes of the variations in the seismic velocities. Furthermore, the spatial patterns obtained with 3D investigations facilitate the recognition of structural features that do not display any intrinsic variation or “signature” in seismic velocities. The 1D τ-p inversion algorithm is widely employed to generate starting models with most computer programs that implement refraction tomography. However, this algorithm emphasizes the vertical resolution of many layers, and as a result, it frequently fails to detect even large lateral variations in This study presents a case that demonstrates the failure of of 1D τ-p inversion algorithm to define or even detect a major shear zone that is 50 m or ten stations wide. , the majority of refraction tomography programs parameterize the seismic velocities within each layer with vertical velocity gradients. By contrast, the 2D generalized reciprocal method (GRM) inversion algorithms emphasize the lateral resolution of individual layers. This study demonstrates the successful detection and definition of the 50-m wide shear zone with the GRM inversion algorithms. The existence of the shear zone is corrobora ted by a 2D analysis of the head wave amplitudes and by numerous closely spaced orthogonal seismic profiles carried out as part of a later 3D refraction investigation. Furthermore, a 1D analysis of the head wave amplitudes indicates that a reversal in the seismic velocities, rather than While all seismic refraction operations should aim to provide as accurate depth estimates as is practical, the major conclusion reached in this study is that refraction inversion algorithms that emphasize the lateral resolution of individual layers generate more useful results for geotechnical and environmental applications. The advantages of the improved lateral resolution are obtained with 2D profiles in which the structural features can be recognized from the magnitudes of the variations in the seismic velocities. Furthermore, the spatial patterns obtained with 3D tracks facilitate the recognition of structural features that do not display any intrinsic variation or “signature ” in seismic velocities.
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