Abstract
The ability to extract information from scattered waves is usually limited to singly scattered energy even if multiple scattering might occur in the medium. As a result, the information in arrival times of higher-order scattered events is underexplored. This information is extracted using fingerprinting theory. This theory has never previously been applied successfully to real measurements, particularly when the medium is dispersive. The theory is used to estimate the arrival times and scattering paths of multiply scattered waves in a thin sheet using an automated scheme in a dispersive medium by applying an additional dispersion compensation method. Estimated times and paths are compared with predictions based on a sequence of straight ray paths for each scattering event given the known scatterer locations. Additionally, numerical modelling is performed to verify the interpretations of the compensated data. Since the source also acts as a scatterer in these experiments, initially, the predictions and the numerical results did not conform to the experimental observations. By reformulating the theory and the processing scheme and adding a source scatterer in the modelling, it is shown that predictions of all observed scattering events are possible with both prediction methods, verifying that the methods are both effective and practically achievable.
Highlights
Scattering is one of the universal physical phenomena that can occur during wave propagation
The ability to extract information from scattered waves is usually limited to singly scattered energy even if multiple scattering might occur in the medium
We show that the method can be used to predict or infer real scattering paths and arrival times of multiply scattered waves in a laboratory
Summary
Scattering is one of the universal physical phenomena that can occur during wave propagation It is caused by the presence of heterogeneities referred to as scatterers, which in an elastic medium might be due to density and/or velocity contrasts. To facilitate the application of the theory to real data, L€oer et al (2015) proposed an automated scheme that relies on several typical seismic data processing techniques such as semblance analysis and stacking. They performed laboratory measurements to test the scheme using steel rods as scatterers embedded in a nondispersive homogeneous medium of polyvinyl alcohol gel. Due to wave attenuation and related dispersion observed in the experimental data, the scheme only detected the first-order and a part of the
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