Exploiting surface consistency for surface-wave characterization and mitigation — Part 1: Theory and 2D examples

Abstract

We have developed a new tomographic inversion method that is able to determine the properties of complex surface waves, which are multimodal and heterogeneous. These properties can be used to generate a detailed near-surface earth model or to predict and remove the surface waves, while protecting reflection signals even with aliased data. The inversion assumes plane-wave physics and generates surface-consistent model parameters as a function of frequency. In this paper, we validate our method with 2D models and data. In a companion paper, we demonstrate its application to 3D data. Inversion for a single mode is linear, but the linearity does not hold at higher frequencies, where multiple modes interfere. However, single-mode inversion results can be used to create a starting model for the subsequent nonlinear multimode tomography. The resulting velocity-frequency grid has greater resolution compared with a beam-forming method. The dispersion curves can be used as input to a subsequent standard 1D surface-wave inversion to generate a velocity-depth model. The tomographic method also determines a grid of attenuation quality factors and variations in the source amplitude and bandwidth, which correlate with the near-surface elevation changes. The amplitude and phase properties can be used together to predict the surface-wave waveforms, which can then be adaptively subtracted from the data on a trace-to-trace basis.

Physically Constrained 2D Joint Inversion of Surface and Body Wave Tomography

“…However, in SWT, each dispersion curve (DC) is estimated between a receiver pair, and the forward operator considers the lateral variability in the computation of the path-averaged slowness between the receiver pair. Due to its ability to produce highresolution 2D or 3D S-wave velocity models, SWT has recently gained considerable attention in near-surface applications (Krohn and Routh, 2017;Papadopoulou et al,2020;Da Col et al, 2020, Khosro Anjom, 2021. However, SWT inversion still suffers from ill-posedness and non-uniqueness.…”

Tackling Lateral Variability Using Surface Waves: A Tomography-Like Approach

“…Duret et al (2016) combined standard P-wave refraction and SWT to compute primary statics for a 3-D narrow-azimuth land dataset. Krohn and Routh (2017a) and Krohn and Routh (2017b) developed a tomography method that evaluates the complex slowness distribution by fitting the trace transfer function, i.e. the waveform change due to the surface waves propagation, and applied it to both 2-D and 3-D densely sampled active data, to predict and subtract the surface-wave signal from the recorded seismograms.…”