Higher-mode contribution is important in surface-wave inversion because it allows more information to be exploited, increases investigation depth, and improves model resolution. A new misfit function for multimodal inversion of surface waves, based on the Haskell-Thomson matrix method, allows higher modes to be taken into account without the need to associate experimental data points to a specific mode, thus avoiding mode-misidentification errors in the retrieved velocity profiles. Computing cost is reduced by avoiding the need for calculating synthetic apparent or modal dispersion curves. Based on several synthetic and real examples with inversion results from the classical and the proposed methods, we find that correct velocity models can be retrieved through the multimodal inversion when higher modes are superimposed in the apparent dispersion-curve or when it is not trivial to determine a priori to which mode each data point of the experimental dispersion curve belongs. The main drawback of the method is related to the presence of several local minima in the misfit function. This feature makes the choice of a consistent initial model very important.
S U M M A R YThe analysis of surface wave propagation is often used to estimate the S-wave velocity profile at a site. In this paper, we propose a stochastic approach for the inversion of surface waves, which allows apparent dispersion curves to be inverted. The inversion method is based on the integrated use of two-misfit functions. A misfit function based on the determinant of the Haskell-Thomson matrix and a classical Euclidean distance between the dispersion curves. The former allows all the modes of the dispersion curve to be taken into account with a very limited computational cost because it avoids the explicit calculation of the dispersion curve for each tentative model. It is used in a Monte Carlo inversion with a large population of profiles. In a subsequent step, the selection of representative models is obtained by applying a Fisher test based on the Euclidean distance between the experimental and the synthetic dispersion curves to the best models of the Monte Carlo inversion. This procedure allows the set of the selected models to be identified on the basis of the data quality. It also mitigates the influence of local minima that can affect the Monte Carlo results. The effectiveness of the procedure is shown for synthetic and real experimental data sets, where the advantages of the two-stage procedure are highlighted. In particular, the determinant misfit allows the computation of large populations in stochastic algorithms with a limited computational cost.
S U M M A R YPure shear wave data are only very rarely acquired for offshore site investigations and exploration. Here, we present details of a novel, seabed-coupled, shear wave vibrator and field data recorded by a densely populated, multicomponent ocean-bottom cable, to improve shallow soil characterization.The prototype shear wave vibrator uses vibroseis technology adopted for marine environments through its instalment on top of a suction anchor, assuring seabed coupling in combination with self-weight penetration. The prototype is depth rated to 1500 m water depth, and can be rotated while installed in the seabed. The philosophy is to acquire fully complementary seismic data to conventional P-and P-to-S-converted waves, in particular for 2-D profiling, VSP (vertical seismic profiling) or monitoring purposes, thereby exploiting advantages of shear waves over compressional waves for determining, for example, anisotropy, small-strain shear modulus and excess pore pressures/effective stress. The source was primarily designed for reservoir depths. However, significant energy is emitted as surface waves, which provide detailed geotechnical information through mapping of shear wave velocities in potentially high resolution of the upper soil units. To fully utilize pure shear wave content, a proper analysis of surface waves is paramount, due to the proximity of surface wave propagation speed with shear wave velocities.The experiment was carried out in the northern North Sea in 364 m water depth. Cable dragging was necessary to obtain close receiver spacing (2.5 m effective spacing), with total line length of 600 m. Frequency-waveform transforms reveal both Scholte and Love waves. Up to six surface wave modes are identified, that is, fundamental mode and several higher surface wave modes. The occurrence of these two different dispersive surface wave types with well-resolved higher modes allows for a unique analysis and inversion scheme for highresolution mapping of physical properties in the shallow subsurface as well as anisotropy, which is discussed in an accompanying paper. The data presented in this paper are thus a unique (long and densely populated receiver array allows for multimodal Love and Scholte surface waves from the marine environment) but challenging (marine operations) marine data set.
SUMMARY Seismic data generated by a novel, seabed‐coupled, shear‐wave vibrator (prototype) and recorded by a densely‐populated, multicomponent ocean‐bottom cable allowed several modes of propagation of Love and Scholte waves to be retrieved in a relatively wide frequency band. Both global dispersion curves and local dispersion curves are extracted in the frequency–wavenumber (f–k) domain and inverted with a multimodal joint Scholte and Love wave inversion algorithm. Monte Carlo inversion is used for a estimating the global S‐wave velocity profile of the seabed sediments whereas laterally constrained inversion is used to detect lateral variations of the layer interface depths. The results are in agreement and allowed consistent full‐waveform simulation to be performed. The investigation depth is limited to around 40 m due to the low shear wave velocities within the shallow clay layer.
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