Integrated GPR attribute analysis for improved thermal structure characterisation of polythermal glaciers

This paper reanalyses and reinterprets the GPR data set collected in 2018 on the Von Postbreen polythermal glacier, in the Tempelfjorden region of the Svalbard Islands. Different Ground Penetrating Radar (GPR) attributes were exploited as tools for the detection of peculiar patterns and inapparent glaciological facies in typical reflection amplitude data. Spectral attributes such as dominant frequency, instantaneous phase and sweetness were specifically calculated. In addition, some texture attributes like chaos and entropy were integrated with the previous ones, so as to enable the detection of a peculiar anomalous zone (AZ). This zone is non-ubiquitous, concentrated in specific areas of the glacier, where the ice is thicker and close to the main bedrock topographic highs. By means of thermal models available in the international literature, this AZ was related to local temperature variations, which are the consequence of increased heat transfer mechanisms due to peculiar stress conditions. The proposed approach can be applied to other glaciological GPR surveys on polythermal glaciers in order to obtain improved and more constrained data interpretation and thermal facies imaging

A first unbiased global determination of polarized PDFs and their uncertainties

We present a first global determination of spin-dependent parton distribution functions (PDFs) and their uncertainties using the NNPDF methodology: NNPDFpol1.1. Longitudinally polarized deep-inelastic scattering data, already used for the previous NNPDFpol1.0 PDF set, are supplemented with the most recent polarized hadron collider data for inclusive jet and $W$ boson production from the STAR and PHENIX experiments at RHIC, and with open-charm production data from the COMPASS experiment, thereby allowing for a separate determination of the polarized quark and anti-quark PDFs, and an improved determination of the medium- and large-$x$ polarized gluon PDF. We study the phenomenological implications of the NNPDFpol1.1 set, and we provide predictions for the longitudinal double-spin asymmetry for semi-inclusive pion production at RHIC.Comment: 36 pages, 16 figures. Final version to be published in Nucl. Phys. B. Small textual improvements and minor typos correcte

SPERIMENTAZIONE DI METODI GEOFISICI INTEGRATI PER L'ANALISI E LA CARATTERIZZAZIONE DI ACQUIFERI IN AMBIENTI COSTIERI

2005/2006XIX Ciclo1972Versione digitalizzata della tesi di dottorato cartacea

Acoustic impedance estimation from combined harmonic reconstruction and interval velocity

Low-frequency components of reflection seismic data are of paramount importance for acoustic impedance inversion, but they typically suffer from a poor signal-to-noise ratio. The estimation of low frequencies of the acoustic impedance can benefit from the combination of a harmonic reconstruction method (based on autoregressive models) and a seismic-derived interval velocity field. We propose the construction of a convex cost-function that accounts for the velocity field, together with geologic a priori information on acoustic impedance and its uncertainty, during the autoregressive reconstruction of the low frequencies. The minimization of this function allows one to reconstruct sensible estimates of low-frequency components of the subsurface reflectivity, which lead to an estimation of acoustic impedance model via a recursive formulation. In particular, the method is suited for an initial and computationally inexpensive assessment of the absolute value of acoustic impedance even when no well log data are available. We first tested the method on layered synthetic models, then we analyzed its applicability and limitations on a real marine seismic dataset that included tomographic velocity information. Despite a strong trace-to-trace variability in the results, which could partially be mitigated by multi-trace inversion, the method demonstrates its capability to highlight lateral variations of acoustic impedance that cannot be detected when the low frequencies only come from well log information

Merging gated Frequency-Modulated Continuous-Wave Mars2020 RIMFAX GPR data

The integration of GPR data at various frequencies, collected with different antennas or with the use of swept-frequency radars opens up interesting perspectives in the study of the subsurface at different resolutions. The proposed methodology is a semi-supervised DL algorithm based on Bi-Directional Long-Short Term Memory to automatically merge varying numbers of data sets at different frequencies. Neural Network training is done directly on the inference data by minimizing a custom loss function based on the L2 norm of all the input data, weighted on the custom merging area and the single output trace. The inference of the trained Neural Network is applied to the same data. The proposed algorithm is tested on synthetic data simulating the Mars conditions and on RIMFAX radar data collected in the Jezero crater during the Mars 2020 mission of Perseverance rover, showing successful performances and robustness