1,721,024 research outputs found
Improved Monte Carlo inversion of surface wave data
No full textInversion of surface wave data suffers from solution non-uniqueness and is hence strongly biased by the initial model. The Monte Carlo approach can handle this nonuniqueness by evidencing the local minima but it is inefficient for high dimensionality problems and makes use of subjective criteria, such as misfit thresholds, to interpret the results. If a smart sampling of the model parameter space, which exploits scale properties of the modal curves, is introduced the method becomes more efficient and with respect to traditional global search methods it avoids the subjective use of control parameters that are barely related to the physical problem. The results are interpreted drawing inference by means of a statistical test that selects an ensemble of feasible shear wave velocity models according to data quality and model parameterization. Tests on synthetic data demonstrate that the application of scale properties concentrates the sampling of model parameter space in high probability density zones and makes it poorly sensitive to the initial boundary of the model parameters. Tests on synthetic and field data, where boreholes are available, prove that the statistical test selects final results that are consistent with the true model and which are sensitive to data quality. The implemented strategies make the Monte Carlo inversion efficient for practical applications and able to effectively retrieve subsoil models even in complex and challenging situations such as velocity inversion
Retrieving lateral variation from surface wave dispersion curve analysis
No full textSurface wave analysis is usually applied as a 1D tool to estimate VS profiles. Here we evaluate the potential of surface wave analysis for the case of lateral variations. Lateral variations can be characterized by exploiting the data redundancy of the ground roll contained in multifold seismic data. First, an automatic processing procedure is applied that allows stacking dispersion curves obtained from different records and which retrieves experimental uncertainties. This is carried out by sliding a window along a seismic line to obtain an ensemble of dispersion curves associated to a series of spatial coordinates. Then, a laterally constrained inversion algorithm is adopted to handle 2D effects, although a 1D model has been assumed for the forward problem solution. We have conducted different tests on three synthetic data sets to evaluate the effects of the processing parameters and of the constraints on the inversion results. The same procedure, applied to the synthetic data, was then tested on a field case. Both the synthetic and field data show that the proposed approach allows smooth lateral variations to be properly retrieved and that the introduction of lateral constraints improves the final result compared to individual inversion
Retrieving 2D structures from surface-wave data by meansof space-varying spatial windowing
No full textSurface-wave techniques are mainly used to retrieve 1D subsurface models. However, in 2D environments, the 1D approach usually neglects the presence of lateral variations and because the surface-wave path crosses different materials, the resulting model is a simplified or misleading description of the site. We tested a processing technique to retrieve 2D structures from surface-wave data acquired with a limited number of receivers. Our technique was based on a twostep process. First, we extracted several local dispersion curves along the survey line using a spatial windowing based on a set of Gaussian windows with different shapes; the window maxima span the survey line so that we were able to extract a dispersion curve from the seismic record for every window. This provided a set of local dispersion curves each of them referring to a different subsurface portion. This space varying spatial windowing provided a good compromise between wavenumber resolution and the lateral resolution of the obtained local dispersion curves. In the second step, we inverted the retrieved set of dispersion curves using a laterally constrained inversion scheme. We applied this procedure to the processing of synthetic and real data sets and the method proved to be successful in reconstructing even complex 2D structures in the subsurfac
Possibilità di Caratterizzare Variazioni Laterali Mediante l'Analisi di Dati di Onde Superficiali
No full text
Retrieving Lateral Variations from Surface Wave Data
No full textThe task of this work is the evaluation of the possibility to identify lateral variation through Surface Wave dispersion analysis even if these techniques are mainly used to characterise 1D subsoil models. This is done exploiting the data redundancy of the ground roll contained in seismic reflection or refraction data through a fully automatic processing procedure that allows to stack dispersion curves obtained from different records and retrieve experimental uncertainties. Hence the dataset to be inverted will be an ensemble of dispersion curves associated to a series of spatial coordinates along the seismic line. In this contest the use of Laterally Constrained Inversion (LCI) algorithm allows to manage such 2D effects in spite of the 1D model assumed for the forward problem solution. Different test have been conducted on different dataset for two synthetic models to evaluate the effects of the processing parameters, of the presence of noise and of lacks of information on the inversion results. All these effects have been observed applying lateral constraints of different strength during the inversion proces
S-wave velocity from P-wave reflection data: the role of surface waves
No full textHigh resolution seismic reflection surveys provide images of subsurface S-wave structures and are therefore a powerful tool for engineering problems. When SH seismic reflection cannot be gathered, shallow S-wave velocity models can be also obtained from surface wave data analysis. Surface waves (either acquired on purpose or extracted from P-wave seismic reflection gathers) can be considered a useful complement or an alternative to seismic reflection for engineering characterization of shallow layers
Joint inversion of Rayleigh-wave dispersion and P-wave refraction data for laterally varying layered models
No full textWe implemented a joint inversion method to build P- and S-wave velocity models from Rayleigh-wave and P-wave refraction data, specifically designed to deal with laterally varying layered environments. A priori information available over the site and any physical law to link model parameters can be also incorporated. We tested and applied the algorithm behind the method. The results from a field data set revealed advantages with respect to individual surface-wave analysis (SWA) and body wave tomography (BWT). The algorithm imposed internal consistency for all the model parameters relaxing the required a priori assumptions (i.e., Poisson's ratio level of confidence in SWA) and the inherent limitations of the two methods (i.e., velocity decreases for BWT
- …
