2D characterization of near-surface V P/V S: surface-wave dispersion inversion versus refraction tomography

International audienceThe joint study of pressure (P-) and shear (S-) wave velocities (Vp and Vs ), as well as their ratio (Vp /Vs), has been used for many years at large scales but remains marginal in near-surface applications. For these applications, and are generally retrieved with seismic refraction tomography combining P and SH (shear-horizontal) waves, thus requiring two separate acquisitions. Surface-wave prospecting methods are proposed here as an alternative to SH-wave tomography in order to retrieve pseudo-2D Vs sections from typical P-wave shot gathers and assess the applicability of combined P-wave refraction tomography and surface-wave dispersion analysis to estimate Vp/Vs ratio. We carried out a simultaneous P- and surface-wave survey on a well-characterized granite-micaschists contact at Ploemeur hydrological observatory (France), supplemented with an SH-wave acquisition along the same line in order to compare Vs results obtained from SH-wave refraction tomography and surface-wave profiling. Travel-time tomography was performed with P- and SH- wave first arrivals observed along the line to retrieve Vtomo p and Vtomo s models. Windowing and stacking techniques were then used to extract evenly spaced dispersion data from P-wave shot gathers along the line. Successive 1D Monte Carlo inversions of these dispersion data were performed using fixed Vp values extracted from Vtomo p the model and no lateral constraints between two adjacent 1D inversions. The resulting 1D Vsw s models were then assembled to create a pseudo-2D Vsw s section, which appears to be correctly matching the general features observed on the section. If the pseudo-section is characterized by strong velocity incertainties in the deepest layers, it provides a more detailed description of the lateral variations in the shallow layers. Theoretical dispersion curves were also computed along the line with both and models. While the dispersion curves computed from models provide results consistent with the coherent maxima observed on dispersion images, dispersion curves computed from models are generally not fitting the observed propagation modes at low frequency. Surface-wave analysis could therefore improve models both in terms of reliability and ability to describe lateral variations. Finally, we were able to compute / sections from both and models. The two sections present similar features, but the section obtained from shows a higher lateral resolution and is consistent with the features observed on electrical resistivity tomography, thus validating our approach for retrieving Vp/Vs ratio from combined P-wave tomography and surface-wave profiling

Joint Inversion of P-waves refraction travel times and surface wave dispersion curves

Rayleigh wave dispersion curves and P refraction travel times are jointly inverted through a damped least square algorithm which accounts simultaneously for both datasets, solving for common thicknesses and respective VP and VS values. The velocities are coupled through the introduction of P-wave velocity values that are used for both the refraction and the surface wave forward modelling. Since the sensitivity of surface waves to P-wave velocity is low, the problem is strongly coupled on the thicknesses and weakly coupled on the velocities. The surface wave - P-wave refraction joint inversion algorithm is effective in solving hidden layer problem, which would lead to big interpretational errors in the case of individual inversion of P dromocrones. The approach is effective for inversion of 1D layered models as shown in one example for the inversion of experimental data, leading to better results than individual inversions also in the case of surface wave

P and S Wave Velocity Model Retrieved by Multi Modal Surface Wave Analysis

Near surface velocity models are needed for static corrections applied to seismic reflection data. Surface wave present in seismic records can be analysed to retrieve near surface models. In particular, the inversion of the dispersion curve related to the fundamental mode of Rayleigh wave propagation is widely used to infer S-wave velocity model but is poorly sensitive to P-wave velocity. The sensitivity to P-wave velocity can be improved including in the inversion higher modes and P-guided waves. An algorithm based on a misfit function related to the Haskell-Thomson determinant is used to handle higher modes and P-guided waves in both a Monte Carlo and a least squares inversion. A preliminary inversion is run, assuming an a priori value of the Poisson ratio, to retrieve a consistent S-wave initial model and then the inversion is run again with the P-wave velocity as a further unknown. The results of both 1D Monte Carlo inversion and pseudo-2D laterally constrained inversion confirm that this approach is a very promising tool for retrieving P and S-wave near surface model

Retrieving Consistent Initial Model for Surface Wave Inversion from Punctual a Priori Information

Inversion of Surface Wave data suffers from solution non uniqueness and is hence strongly biased by the initial model. A priori geological information can be used to produce a reliable initial model: these information, however, are rarely available along all the survey line since they are mainly punctual information. Moreover, when we perform a laterally constrained inversion we have to be aware that bad quality data, though localized in a limited region of the entire dataset, can bias the whole result. In this work we present a procedure to estimate the quality of the Surface Wave dataset before the inversion and to produce a consistent initial model for the LCI. We prepared some tools to make the quality control of dataset semi-automatic: besides, we arranged a method to extend a priori punctual information to the whole survey line, in order to generate a pseudo 2D initial model able to make the inversion process more reliable. This method is based on a sensitivity analysis and on the application of scale properties of Surface Waves. Our procedure ensures a better model parameters estimation, makes the inversion process faster and allows a proper tuning of the strength of lateral constraints in LCI

Retrieving 2D Structures from Surface Wave Data by Means of a Space-varying Spatial Windowing

The Surface Wave (SW) techniques are mainly used to retrieve 1D subsoil models. However, in 2D environments the 1D approach usually neglects the presence of lateral variations and, since the SW path crosses different materials, the resulting model is a simplified description of the site. We propose a processing technique to retrieve 2D structures from SW acquired with a limited number of receivers. Our technique is based on a two step process: first of all several local dispersion curves are extracted along the survey line using a spatial windowing based on a set of Gaussian windows with different shape; the windows maxima span the survey line so that for every window a dispersion curve can be extracted from the seismogram, thus retrieving a set of dispersion curves each of them referring to a different subsoil portion. This space-varying spatial windowing provides a good compromise between wavenumber resolution and the lateral resolution of the obtained local dispersion curves. In the second step of our procedure the retrieved set of dispersion curves is inverted using a laterally constrained inversion (LCI) scheme. This procedure has proven to be effective for the processing of both real and synthetic data