Micro-geophysics to assess the integrity of some statues in the Museo Egizio of Turin, Italy

On request of the Soprintendenza in charge of the Museo Egizio of Turin, a quite large number of tests have been performed on four statues of the museum to assess their integrity both for practical (moving the statue) and archaeological purposes. Ultrasonic tomography and georadar have been used with fine results on sub-decimeter scale. In this paper we present the main results on the statues of the Pharaons Ramses II (Fig.1 left) and Tuthmosis I. (Fig.2 left). Both the statues belong to the collection set up by Bernardino Drovetti, Console Generale of France in Egypt in the early XIX century. Ramses II statue was restored in the first half of the XIX century. Few documents can be found on these restoration works: very likely the statue arrived broken to Turin and was reassembled with cement mortar (Hartleben, 1909) No news can be found neither on the type of mortar nor on the quantity of mortar actually used. The statue of Ramses was probably found at Tebe in 1818. It is made by basanite exploited from a quarry in Uadi Hammamat. The basanite is a basaltic extrusive rock also known as Lydian stone or lydite. It was almost exclusively reserved to the crafting of statues of pharaons or divinities. In many parts of the statue the mortar (as dark as the stone) is clearly visible (Fig.1 right). The statue of Tutmosis I was found by J.J. Rifaud , a Drovetti 's agent, in 1818 in Tebe, very likely in the Karnak temple. The king sits on a throne with many scripts on both the sides of the seat. The statue is made by a dark diorite with some light pink plagioclase crystals sizing few centimeters. Its conservation seems fairly goo

Application and comparison of three tomographic techniques for detection of decay in trees

This paper reports application of electric, ultrasonic, and georadar tomography for detection of decay in trees and their comparison with the traditional penetrometer. Their feasibility in arboriculture is also evaluated, critically considering some "open problems." The experiments were carried out in an urban environment on two plane (Platanus hybrida Brot.) trees. Both trees, after felling, showed extensive white rot in the central cylinder. The electric tomography revealed low resistivity zones roughly centered in the trunk. A comparison with the successively cut sections showed a fine correspondence to decayed areas and a strong correspondence between high moisture zones and low resistivity zones. Ultrasonic tomography demonstrated to be a very effective tool for the detection of internal decay, accurately locating the position of the anomalies and estimating their size, shape, and characteristic in terms of mechanical properties. With the georadar technique, the high contrast of electromagnetic impedance measured between the inner decayed section and the outside sound section allowed the detection of the interface between the sound and decayed section of the tree, using radar acquisition in reflection modality. The penetrometer profiles detected the low-resistance areas inside the two trunk

P-wave and surface wave survey for permafrost analysis in alpine regions

We discuss the results of seismic survey to delineate temporal and spatial changes of frozen layer in Alpine environments. The seismic characterization allows us to detect changes of soil deformability properties related to the temperature effect on subsoi

Surface wave analysis for building near surface velocity models: established approaches and new perspectives

Today, surface-wave analysis is widely adopted for building near-surface S-wave velocity models. The surface-wave method is under continuous and rapid evolution, also thanks to the lively scientific debate among different disciplines, and interest in the technique has increased significantly during the last decade. A comprehensive review of the literature in the main scientific journals provides historical perspective, methodological issues, applications, and most-promising recent approaches. Higher modes in the inversion and retrieval of lateral variations are dealt with in great detail, and the current scientific debate on these topics is reported.Abest-practices guideline is also outline

Machine Learning for Seismic Exploration: where are we and how far are we from the Holy Grail?

Machine Learning (ML) applications in seismic exploration are growing faster than applications in other industry fields, mainly due to the large amount of acquired data for the exploration industry. The ML algorithms are constantly being implemented to almost all the steps involved in seismic processing and interpretation workflow, mainly for automation, processing time reduction, efficiency and in some cases for improving the results. We carried out a literature-based analysis of existing ML-based seismic processing and interpretation published in SEG and EAGE literature repositories and derived a detailed overview of the main ML thrusts in different seismic applications. For each publication, we extracted various metadata about ML implementations and performances. The data indicate that current ML implementations in seismic exploration are focused on individual tasks rather than a disruptive change in processing and interpretation workflows. The metadata shows that the main targets of ML applications for seismic processing are denoising, velocity model building and first break picking, whereas for seismic interpretation, they are fault detection, lithofacies classification and geo-body identification. Through the metadata available in publications, we obtained indices related to computational power efficiency, data preparation simplicity, real data test rate of the ML model, diversity of ML methods, etc. and we used them to approximate the level of efficiency, effectivity and applicability of the current ML-based seismic processing and interpretation tasks. The indices of ML-based processing tasks show that current ML-based denoising and frequency extrapolation have higher efficiency, whereas ML-based QC is more effective and applicable compared to other processing tasks. Among the interpretation tasks, ML-based impedance inversion shows high efficiency, whereas high effectivity is depicted for fault detection. ML-based Lithofacies classification, stratigraphic sequence identification and petro/rock properties inversion exhibit high applicability among other interpretation tasks

Joint inversion of seismic and electric data applied to 2D media

Methods based on the seismic P-wave, seismic surface wave, and apparent resistivity are commonly used in the solution of several near-surface problems. However, the solution nonuniqueness and the intrinsic limitations of these methods can cause inconsistency in the final results. Dispersion curves of surface waves, P-wave traveltimes, and apparent-resistivity data were jointly inverted to obtain internally consistent and more reliable final model of P- and S-wave velocities and resistivity. A collection of 1D layered models was obtained by a deterministic joint inversion algorithm based on the laterally constrained inversion scheme. The three data sets were jointly inverted imposing the same structure and Poisson’s ratio was introduced as a physical link between P- and S-wave velocities to better constrain the inversion. No physical link was imposed between the resistivity and the seismic velocities. The inversion algorithm was tested on synthetic data and then applied to a field case, where benchmark borehole data were available. The synthetic and field examples provided results in agreement with the true model and the existing geologic information, respectively