Estimation of soil properties using waveforms of seismic surface waves

Abstract

A method for transforming seismic surface waves into depth profiles of dynamic properties of the soil such as the soil shear modulus or wave velocity or wave attenuation. The invention uses seismic data recorded preferably with a plurality of sources and receivers with a two-stage inversion approach. First, variations in surface-wave waveforms are decomposed (303) into surface-consistent transfer functions preferably for each source, each receiver, and each small region (301) of the surface. Then the transfer functions for each region are inverted (308) to determine soil properties or near-surface properties (such as the shear modulus) as a function of depth. The method can solve for the complex multi-mode nature of the surface waves for a media with both vertical and lateral changes in properties. Errors and limits in resolution for traditional methods from misidentification of ground roll modes or from assuming laterally uniform soil properties are avoided.

Description

technical field [0001] This application claims the benefit of US Provisional Application 61 / 087,933, filed August 11,2008. [0002] The present invention relates generally to the field of geophysical prospecting, and more particularly to seismic data processing. Specifically, the present invention is a method for inverting seismic surface wave data to obtain elastic properties of soil, such as soil shear wave velocity or shear modulus or shear Cut wave attenuation. In particular, elastic properties or depth profile properties can be obtained as a function of depth from the surface. The method can also be used to assess the location of anomalies within the soil, such as holes or buried objects. Background technique [0003] Seismic surface waves, also known as ground-roll or Rayleigh waves or Love waves, are confined to regions close to the Earth's surface, and thus their propagation depends on the Surface elastic properties, particularly shear wave velocity as a function...

AI Technical Summary

Problems solved by technology

[0006] The problem with all prior art methods using surface waves, Rayleigh waves or Love waves is that it is difficult to solve or distinguish the different dispersion curves for different surface wave modes

An inherent difficulty arises from frequency and velocity uncertainties, and inversion suffers when wrong modes are identified or incorrectly chosen

The second difficulty arises from the lack of knowledge of the phase of the source and the uncertainty of phase changes above 2π

[0020] There are many algorithms available for solving near-surface velocity distributions from dispersion curves, but the success of all these methods depends on the accuracy of the input dispersion curves

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