A computer code for forward calculation and inversion of the H/V spectral ratio under the diffuse field assumption

During a quarter of a century, the main characteristics of the horizontal-to-vertical spectral ratio of ambient noise HVSRN have been extensively used for site effect assessment. In spite of the uncertainties about the optimum theoretical model to describe these observations, several schemes for inversion of the full HVSRN curve for near surface surveying have been developed over the last decade. In this work, a computer code for forward calculation of H/V spectra based on the diffuse field assumption (DFA) is presented and tested.It takes advantage of the recently stated connection between the HVSRN and the elastodynamic Green's function which arises from the ambient noise interferometry theory. The algorithm allows for (1) a natural calculation of the Green's functions imaginary parts by using suitable contour integrals in the complex wavenumber plane, and (2) separate calculation of the contributions of Rayleigh, Love, P-SV and SH waves as well. The stability of the algorithm at high frequencies is preserved by means of an adaptation of the Wang's orthonormalization method to the calculation of dispersion curves, surface-waves medium responses and contributions of body waves. This code has been combined with a variety of inversion methods to make up a powerful tool for passive seismic surveying.Comment: Published in Computers & Geosciences 97, 67-7

Highly efficient Bayesian joint inversion for receiver-based data and its application to lithospheric structure beneath the southern Korean Peninsula

With the deployment of extensive seismic arrays, systematic and efficient parameter and uncertainty estimation is of increasing importance and can provide reliable, regional models for crustal and upper-mantle structure.We present an efficient Bayesian method for the joint inversion of surface-wave dispersion and receiver-function data that combines trans-dimensional (trans-D) model selection in an optimization phase with subsequent rigorous parameter uncertainty estimation. Parameter and uncertainty estimation depend strongly on the chosen parametrization such that meaningful regional comparison requires quantitative model selection that can be carried out efficiently at several sites. While significant progress has been made for model selection (e.g. trans-D inference) at individual sites, the lack of efficiency can prohibit application to large data volumes or cause questionable results due to lack of convergence. Studies that address large numbers of data sets have mostly ignored model selection in favour of more efficient/simple estimation techniques (i.e. focusing on uncertainty estimation but employing ad-hoc model choices). Our approach consists of a two-phase inversion that combines trans-D optimization to select the most probable parametrization with subsequent Bayesian sampling for uncertainty estimation given that parametrization. The trans-D optimization is implemented here by replacing the likelihood function with the Bayesian information criterion (BIC). The BIC provides constraints on model complexity that facilitate the search for an optimal parametrization. Parallel tempering (PT) is applied as an optimization algorithm. After optimization, the optimal model choice is identified by the minimum BIC value from all PT chains. Uncertainty estimation is then carried out in fixed dimension. Data errors are estimated as part of the inference problem by a combination of empirical and hierarchical estimation. Data covariance matrices are estimated from data residuals (the difference between prediction and observation) and periodically updated. In addition, a scaling factor for the covariance matrix magnitude is estimated as part of the inversion. The inversion is applied to both simulated and observed data that consist of phase- and group-velocity dispersion curves (Rayleigh wave), and receiver functions. The simulation results show that model complexity and important features are well estimated by the fixed dimensional posterior probability density. Observed data for stations in different tectonic regions of the southern Korean Peninsula are considered. The results are consistent with published results, but important features are better constrained than in previous regularized inversions and are more consistent across the stations. For example, resolution of crustal and Moho interfaces, and absolute values and gradients of velocities in lower crust and upper mantle are better constrained

Simulation of sea-state sequences

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The present PhD study, in its first part, uses artificial neural networks (ANNs), an optimization technique called simulated annealing, and statistics to simulate the significant wave height (Hs) and mean zero-up-crossing period ( ) of 3-hourly sea-states of a location in the North East Pacific using a proposed distribution called hepta-parameter spline distribution for the conditional distribution of Hs or given some inputs. Two different seven- network sets of ANNs for the simulation and prediction of Hs and were trained using 20-year observed Hs’s and ’s. The preceding Hs’s and ’s were the most important inputs given to the networks, but the starting day of the simulated period was also necessary. However, the code replaced the day with the corresponding time and the season. The networks were trained by a simulated annealing algorithm and the outputs of the two sets of networks were used for calculating the parameters of the probability density function (pdf) of the proposed hepta-parameter distribution. After the calculation of the seven parameters of the pdf from the network outputs, the Hs and of the future sea-state is predicted by generating random numbers from the corresponding pdf. In another part of the thesis, vertical piles have been studied with the goal of identifying the range of sea-states suitable for the safe pile driving operation. Pile configuration including the non-linear foundation and the gap between the pile and the pile sleeve shims were modeled using the finite elements analysis facilities within ABAQUS. Dynamic analyses of the system for a sea-state characterized by Hs and and modeled as a combination of several wave components were performed. A table of safe and unsafe sea-states was generated by repeating the analysis for various sea-states. If the prediction for a particular sea-state is repeated N times of which n times prove to be safe, then it could be said that the predicted sea-state is safe with the probability of 100(n/N). The last part of the thesis deals with the Hs return values. The return value is a widely used measure of wave extremes having an important role in determining the design wave used in the design of maritime structures. In this part, Hs return value was calculated demonstrating another application of the above simulation of future 3-hourly Hs’s. The maxima method for calculating return values was applied in such a way that avoids the conventional need for unrealistic assumptions. The significant wave height return value has also been calculated using the convolution concept from a model presented by Anderson et al. (2001)

Oceanic lithosphere-asthenosphere boundaryfrom surface wave dispersion data

International audienceAbstract According to different types of observations, the nature of lithosphere-asthenosphereboundary (LAB) is controversial. Using a massive data set of surface wave dispersions in a broad periodrange (15–300 s), we have developed a three-dimensional upper mantle tomographic model (first-orderperturbation theory) at the global scale. This is used to derive maps of the LAB from the resolved elasticparameters. The key effects of shallow layers and anisotropy are taken into account in the inversion process.We investigate LAB distribution primarily below the oceans, according to different kinds of proxies thatcorrespond to the base of the lithosphere from the shear velocity variation at depth, the amplituderadial anisotropy, and the changes in azimuthal anisotropy G orientation. The estimations of the LAB depthbased on the shear velocity increase from a thin lithosphere (∼20 km) in the ridges, to a thick old-oceanlithosphere (∼120–130 km). The radial anisotropy proxy shows a very fast increase in the LAB depth fromthe ridges, from ∼50 km to the older ocean where it reaches a remarkable monotonic subhorizontal profile(∼70–80 km). The LAB depths inferred from the azimuthal anisotropy proxy show deeper values for theincreasing oceanic lithosphere (∼130–135 km). The difference between the evolution of the LAB depth withthe age of the oceanic lithosphere computed from the shear velocity and azimuthal anisotropy proxies andfrom the radial anisotropy proxy raises questions about the nature of the LAB in the oceanic regions and ofthe formation of the oceanic plate

Improved parameterization to invert Rayleigh-wave data for shallow profiles containing stiff inclusions

Inversion of shear-wave velocity profiles from phase-velocity measurements of Rayleigh-wave energy for sites containing stiff layers can be erroneous if such layers are not characterized in the starting or reference model. Incorporation of a priori knowledge then is key for converging upon a realistic or meaningful solution. Resolving soil profiles in desert regions where stiff layers cemented with calcium carbonate are intermixed with softer, uncemented media is an application for which locating shallow stiff inclusions has important implications. Identification of the stiff layers is critical for foundation design and cost estimating of excavations. A parameterization that seems adequate for this problem is to solve for anticipated high-stiffness layers embedded in a coarser (background) profile that captures the general shear-wave velocity trend of the study area. The optimization is accomplished by using simulated annealing. Uncertainty measures resulting from the inversion are helpful for describing the influence of the parameterization on final model estimates

Advanced analysis of complex seismic waveforms to characterize the subsurface Earth structure

This thesis includes three major parts, (1) Body wave analysis of mantle structure under the Calabria slab, (2) Spatial Average Coherency (SPAC) analysis of microtremor to characterize the subsurface structure in urban areas, and (3) Surface wave dispersion inversion for shear wave velocity structure. Although these three projects apply different techniques and investigate different parts of the Earth, their aims are the same, which is to better understand and characterize the subsurface Earth structure by analyzing complex seismic waveforms that are recorded on the Earth surface. My first project is body wave analysis of mantle structure under the Calabria slab. Its aim is to better understand the subduction structure of the Calabria slab by analyzing seismograms generated by natural earthquakes. The rollback and subduction of the Calabrian Arc beneath the southern Tyrrhenian Sea is a case study of slab morphology and slab-mantle interactions at short spatial scale. I analyzed the seismograms traversing the Calabrian slab and upper mantle wedge under the southern Tyrrhenian Sea through body wave dispersion, scattering and attenuation, which are recorded during the PASSCAL CAT/SCAN experiment. Compressional body waves exhibit dispersion correlating with slab paths, which is high-frequency components arrivals being delayed relative to low-frequency components. Body wave scattering and attenuation are also spatially correlated with slab paths. I used this correlation to estimate the positions of slab boundaries, and further suggested that the observed spatial variation in near-slab attenuation could be ascribed to mantle flow patterns around the slab. My second project is Spatial Average Coherency (SPAC) analysis of microtremors for subsurface structure characterization. Shear-wave velocity (Vs) information in soil and rock has been recognized as a critical parameter for site-specific ground motion prediction study, which is highly necessary for urban areas located in seismic active zones. SPAC analysis of microtremors provides an efficient way to estimate Vs structure. Compared with other Vs estimating methods, SPAC is noninvasive and does not require any active sources, and therefore, it is especially useful in big cities. I applied SPAC method in two urban areas. The first is the historic city, Charleston, South Carolina, where high levels of seismic hazard lead to great public concern. Accurate Vs information, therefore, is critical for seismic site classification and site response studies. The second SPAC study is in Manhattan, New York City, where depths of high velocity contrast and soil-to-bedrock are different along the island. The two experiments show that Vs structure could be estimated with good accuracy using SPAC method compared with borehole and other techniques. SPAC is proved to be an effective technique for Vs estimation in urban areas. One important issue in seismology is the inversion of subsurface structures from surface recordings of seismograms. My third project focuses on solving this complex geophysical inverse problems, specifically, surface wave phase velocity dispersion curve inversion for shear wave velocity. In addition to standard linear inversion, I developed advanced inversion techniques including joint inversion using borehole data as constrains, nonlinear inversion using Monte Carlo, and Simulated Annealing algorithms. One innovative way of solving the inverse problem is to make inference from the ensemble of all acceptable models. The statistical features of the ensemble provide a better way to characterize the Earth model