Seismic diffraction separation in the near surface: Detection of high-contrast voids in unconsolidated soils

Authors: BAKHTIARI RAD, PARSA - University Of Mississippi; HICKEY, CRAIG - University Of Mississippi

Submitted to: Geophysics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/19/2020
Publication Date: 3/11/2021
Citation: Bakhtiari Rad, P., Hickey, C.J. 2021. Seismic diffraction separation in the near surface: Detection of high-contrast voids in unconsolidated soils. Geophysics. 86(3):WB13-WE23. https://library.seg.org/doi/10.1190/geo2020-0366.1.

Interpretive Summary: Seismic waves travel through the ground much like sound waves travel through the air, and can be measured using geophones instead of microphones. Seismic waves can be generated in the ground by using a seismic source, such as a large hammer or mechanical shaker. By placing geophones around a seismic source, the data collected can be used to help identify certain underground features. This paper investigates advanced data processing techniques to enhance the detection of undergound voids, such as tunnels or culverts. These techniques involve observations of reflections and refractions in the seismic waves. These techniques can be used to find faults in earthen dams that may pose a threat to people whose homes may be flooded in the event of a dam break. They can also be used to find buried pipes or other objects that would otherwise require extensive digging to find.

Technical Abstract: Seismic diffractions carry the signature of near-surface high-contrast anomalies and need to be extracted from the data to complement the reflection processing and other geophysical techniques. Because diffractions are often masked by reflections, surface waves, and noise, careful diffraction separation is required as a first step for diffraction imaging. A multiparameter time-imaging method is used to separate near-surface diffractions. The implemented scheme makes use of the wavefront attributes that are reliable fully data-derived processing parameters. To mitigate the effect of strong noise and wavefield interference in near-surface data, our workflow incorporates two wavefront-based parameters, dip angle and coherence, as additional constraints. The output of the diffraction separation is a time trace-based stacked section that provides the basis for further analysis and applications such as time migration. To evaluate the performance of the proposed wavefront-based workflow, it is applied to two challenging field data sets that were collected over small culverts in very near-surface soft soil environments. The results of the proposed constrained workflow and the existing unconstrained approach are presented and compared. The proposed workflow demonstrates superiority over the existing method by attenuating more reflection and noise, leading to improved diffraction separation. The abundance of unmasked diffractions reveals that the very near surface is highly scattering. Time migration is carried out to enhance anomaly detection by focusing the isolated diffractions. Although strong diffractivity is observed at the approximate location of the targets, there are other diffracting zones observed in the final sections that might bring uncertainties for interpretation.