Exploring some issues in acoustic full waveform inversion

The least‐squares error measures the difference between observed and modelled seismic data. Because it suffers from local minima, a good initial velocity model is required to avoid convergence to the wrong model when using a gradient‐based minimization method. If a data set mainly contains reflection events, it is difficult to update the velocity model with the least‐squares error because the minimization method easily ends up in the nearest local minimum without ever reaching the global minimum. Several authors observed that the model could be updated by diving waves, requiring a wide‐angle or large‐offset data set. This full waveform tomography is limited to a maximum depth. Here, we use a linear velocity model to obtain estimates for the maximum depth. In addition, we investigate how frequencies should be selected if the seismic data are modelled in the frequency domain. In the presence of noise, the condition to avoid local minima requires more frequencies than needed for sufficient spectral coverage. We also considered acoustic inversion of a synthetic marine data set created by an elastic time‐domain finite‐difference code. This allowed us to validate the estimates made for the linear velocity model. The acoustic approximation leads to a number of problems when using long‐offset data. Nevertheless, we obtained reasonable results. The use of a variable density in the acoustic inversion helped to match the data at the expense of accuracy in the inversion result for the density.     

Initial formation of channel–shoal patterns in double–inlet systems

Ocean Dynamics - Channel–shoal patterns are often observed in the back–barrier basins of inlet systems and are important from both an economical and ecological point of view. Focussing...     

Research Note: A workaround for the corner problem in numerically exact non-reflecting boundary conditions

Simulations of wave propagation in the Earth usually require truncation of a larger domain to the region of interest to keep computational cost acceptable. This introduces artificial boundaries that should not generate reflected waves. Most existing boundary conditions are not able to completely suppress all the reflected energy, but suffice in practice except when modelling subtle events such as interbed multiples. Exact boundary conditions promise better performance but are usually formulated in terms of the governing wave equation and, after discretization, still may produce unwanted artefacts. Numerically exact non-reflecting boundary conditions are instead formulated in terms of the discretized wave equation. They have the property that the numerical solution computed on a given domain is the same as one on a domain enlarged to the extent that waves reflected from the boundary do not have the time to reach the original truncated domain. With a second- or higher-order finite-difference scheme for the one-dimensional wave equation, these boundary conditions follow from a recurrence relation. In its generalization to two or three dimensions, a recurrence relation was only found for a single non-reflecting boundary on one side of the domain or two of them at opposing ends. The other boundaries should then be zero Dirichlet or Neumann. If two non-reflecting boundaries meet at a corner, translation invariance is lost and a simple recurrence relation could not be found. Here, a workaround is presented that restores translation invariance by imposing classic, approximately non-reflecting boundary conditions on the other sides and numerically exact ones on the two opposing sides that otherwise would create the strongest reflected waves with the classic condition. The exact ones can also be applied independently. As a proof of principle, the method is applied to the two-dimensional acoustic wave equation, discretized on a rectangular domain with a second-order finite-difference scheme and first-order Enquist–Majda boundary conditions as approximate ones. The method is computationally costly but has the advantage that it can be reused on a sequence of problems as long as the time step and the sound speed values next to the boundary are kept fixed.     

Bayesian inversion of joint SH seismic and seismoelectric data to infer glacier system properties

In glacial studies, properties such as glacier thickness and the basement permeability and porosity are key to understand the hydrological and mechanical behaviour of the system. The seismoelectric method could potentially be used to determine key properties of glacial environments. Here we analytically model the generation of seismic and seismoelectric signals by means of a shear horizontal seismic wave source on top of a glacier overlying a porous basement. Considering a one-dimensional setting, we compute the seismic waves and the electrokinetically induced electric field. We then analyse the sensitivity of the seismic and electromagnetic data to relevant model parameters, namely depth of the glacier bottom, porosity, permeability, shear modulus and saturating water salinity of the glacier basement. Moreover, we study the possibility of inferring these key parameters from a set of very low noise synthetic data, adopting a Bayesian framework to pay particular attention to the uncertainty of the model parameters mentioned above. We tackle the resolution of the probabilistic inverse problem with two strategies: (1) we compute the marginal posterior distributions of each model parameter solving multidimensional integrals numerically and (2) we use a Markov chain Monte Carlo algorithm to retrieve a collection of model parameters that follows the posterior probability density function of the model parameters, given the synthetic data set. Both methodologies are able to obtain the marginal distributions of the parameters and estimate their mean and standard deviation. The Markov chain Monte Carlo algorithm performs better in terms of numerical stability and number of iterations needed to characterize the distributions. The inversion of seismic data alone is not able to constrain the values of porosity and permeability further than the prior distribution. In turn, the inversion of the electric data alone, and the joint inversion of seismic and electric data are useful to constrain these parameters as well as other glacial system properties. Furthermore, the joint inversion reduces the uncertainty of the model parameters estimates and provides more accurate results.     

Landslide susceptibility mapping by remote sensing and geomorphological data: case studies on the Sorrentina Peninsula (Southern Italy)

The Sorrentina Peninsula is a densely populated area with high touristic impact. It is located in a morphologically complex zone of Southern Italy frequently affected by dangerous and calamitous landslides. This work contributes to the prevention of such natural disasters by applying a GIS-based interdisciplinary approach aimed to map the areas more potentially prone to trigger slope instability phenomena. We have developed the Landslide Susceptibility Index (LSI) combining five weighted and ranked susceptibility parameters on a GIS platform. These parameters are recognized in the literature as the main predisposing factors for triggering landslides. This work combines analyses conducted on Remote Sensing, Geo-Lithology and Morphometry data and it is organized in the following logical steps: i) Multi-temporal InSAR technique was applied to Envisat-ASAR (2003–2010) and COSMO-SkyMed (2013–2015) datasets to obtain the ground displacement time series and the relative mean ground velocity maps. InSAR allowed the detection of the areas that are subjected to ground deformation and the main affected municipalities; ii) Such deformation areas were investigated through airborne photo interpretation to identify the presence of geomorphological peculiarities connected to potential slope instability. Subsequently, some of these peculiarities were checked on the field; iii) In these deformation areas the susceptibility parameters were mapped in the entire territory of Amalfi and Conca dei Marini and then investigated with a multivariate analysis to derive the classes and the respective weights used in the LSI calculation. The resulting LSI map classifies the two municipalities with high spatial resolution (2m) according to five classes of instability. The map highlights that the high/very high susceptibility zones cover 6% of the investigated territory and correspond to potential landslide source areas characterized by 25°-70° slope angles. A spatial analysis between the map of the historical landslides and the areas classified according to susceptibility allowed testing of the reliability of the LSI Index, resulting in 85% prediction accuracy.     

Transatlantic latest Cretaceous mosasaurs (Reptilia,Lacertilia) from the Maastrichtian type area and New Jersey

Cranial and postcranial elements of the mosasaurid reptiles Mosasaurus hoffmanni Mantell 1829 and Plioplatecarpus marshi Dollo 1882 from the Maastrichtian type area, and of Mosasaurus maximus Cope 1869 and Plioplatecarpus depressus (Cope 1869) from New Jersey are compared. Views held by previous authors are discussed. It is concluded that these European and North American taxa are conspecific.     

Ultrasound assisted extraction and determination of the carbohydrate fraction in marine sediments

In this paper, an ultrasound–acetic acid procedure for the simultaneous extraction and hydrolysis of carbohydrates in marine sediments prior to their colorimetric determination is described. The main advantage of the proposed procedure is the improved analytical accuracy achieved. Extraction and hydrolysis are quantitative since the oxidative reactions which cause the underestimation of the total carbohydrate amount are minimized. Moreover the procedure is fast, requiring only 5 h for the whole analysis (extraction, hydrolysis and colorimetric determination by the phenol-sulphuric acid method). The proposed procedure has recoveries generally higher than 80% and gives comparable results with the conventional 24 h HCl extraction.     

The influence of geological, geochemical, and biogenic habitat heterogeneity on seep biodiversity

Cold seeps are among the most heterogeneous of all continental margin habitats. Abiotic sources of heterogeneity in these systems include local variability in fluid flow, geochemistry, and substrate type, which give rise to different sets of microbial communities, microbial symbiont-bearing foundation species, and associated heterotrophic species. Biogenic habitats created by microbial mats and the symbiotic species including vesicomyid clams, bathymodiolin mussels, and siboglinid tubeworms add an additional layer of complexity to seep habitats. These forms of habitat heterogeneity result in a variety of macrofaunal and meiofaunal communities that respond to changes in structural complexity, habitat geochemistry, nutrient sources, and interspecific interactions in different ways and at different scales. These responses are predicted by a set of theoretical metacommunity models, the most appropriate of which for seep systems appears to be the 'species sorting' concept, an extension of niche theory. This concept is demonstrated through predictable patterns of community assembly, succession, and beta-level diversity. These processes are described using a newly developed analytical technique examining the change in the slope of the species accumulation curve with the number of habitats examined. The diversity response to heterogeneity has a consistent form, but quantitatively changes at different seep sites around the world as the types of habitats present and the size-classes of fauna analyzed change. The increase in beta diversity across seep habitat types demonstrates that cold seeps and associated biogenic habitats are significant sources of heterogeneity on continental margins globally.     

Uranium in Saline Lakes of Mongolia and Adjacent Areas

正1 Introduction Increasing demand for uranium raw materials for the nuclear industry has stimulated interest in non-traditional sources,including hydromineral ones[Qin,2009].Those are saline lakes located in the uranium ore districts.Accumulation of uranium in such lakes results from the leaching of uranium from the rocks by surface and ground