Application of the relocation-error distribution on geomagnetic databases. Analyses on the «Historical Italian Geomagnetic Data Catalogue»

The reliability of the Historical Italian Geomagnetic Data Catalogue, comprising 536 directions and 393 intensities, has been assessed by comparing the historical geomagnetic measurements with the GUFM1 model predictions. Such measurements were assessed at three selected relocation centres. For all the data contained in the Catalogue it has been calculated the discrepancy between the relocated data and the GUFM1-model prediction at the relocation centres. There is a correlation between relocation distance and the mean discrepancy. The upper limit of discrepancy assumable as relocation error has been selected using error distributions previously calculated using geomagnetic field models. Angular and intensity threshold lines have been slightly shifted upwards to account for the estimated error of GUFM1 model itself at the considered region, mainly due to the crustal field. The Italian database proved to contain reliable data, as only a very low percentage of data (namely 14 directions and 20 intensities) can be considered anomalous. Possible explanations for such questionable data are suggested. All the remaining data of this catalogue could thus be added to the databases used to produce regional or global geomagnetic models

Backpropagation neural network approaches for assessing petrophysical properties of a carbonate reservoir in southeast Brazil

This article applies backpropagation neural network algorithms to estimate petrophysical parameters, including lithology, porosity, permeability, and water saturation, in southeast Brazil’s post-salt Albian carbonate reservoir. Geophysical well logs (gamma ray, bulk density, neutron porosity, deep resistivity, and sonic), petrophysical laboratory data (porosity and permeability), and geologicalinformation comprised the experimental datasets, while the water saturation was calculated with Archie’s equation. Firstly, rapid interpretation of field and laboratory data provided preliminary reservoir characterization, including boundaries and average porosity. Three backpropagation neural network algorithms were then implemented to assess the petrophysical parameters. During training, validation, and testing on reference hole LI10, Levenberg-Marquardt, Scaled Conjugate Gradient, and Bayesian Regularization techniques were used to fit the petrophysical parameters using the logs as input. Results demonstrate accurate and efficient processes, with high Pearson’s correlation coefficients and variable mean square error values across all parameters. Estimationof lithology, water saturation, and porosity achieved high accuracy with all algorithms, while permeability posed the greatest challenge. Bayesian Regularization yielded the best performance, followed by Levenberg-Marquardt and Scaled Conjugate Gradient, though all produced reasonable estimates. Successful blind test at well LI03 confirms these techniques as promising approaches forpetrophysical characterization

A Multi-method Geophysical Approach for Complex Shallow Landslide Characterization

This case study demonstrates the value of combining multiple non-invasive geophysical methods to characterize a landslide along Highway 7 near Jasper, Arkansas, USA. Geophysical testing was conducted using Multichannel Analysis of Surface Waves (MASW), Horizontal to VerticalSpectral Ratio (HVSR), and Electrical Resistivity Tomography (ERT), supplemented by select soil borings. The geophysical investigation aimed to provide a high-resolution, near-continuous view of subsurface conditions, including bedrock depth and the location of the groundwater table or highly saturated zones within the slide area. These factors are important contributors to slope instability. The MASW results revealed a highly variable depth to weathered bedrock along the observed displacement zone, with the bedrock becoming shallower downslope. The ERT data detected saturated zones associated with observed seeps and springs in the area, which were feeding water into the unstable zone. A low resistivity zone on the north side correlated to wet spots, while south of the highway, saturation occurred near the deeper bedrock interface. Additionally, a grid-based HVSR approach generated a high-resolution image of the shallow and complex bedrock topography across the slide area, providing valuable information for the slope repair design. Overall, the integrated geophysical approach offered a more sustainable, rapid, and cost-effective solution for comprehensive landslide characterization and slope stability assessment, compared to relying solely on conventional methods. The combined geophysical results provided a detailed, high-resolution understanding of the subsurface conditions influential for stability analyses and slope repair design

Offshore Shear Wave Velocity Measurements for the Assessment of Soil Sampling Quality

Shear wave velocity Vs is a critical soil parameter for several geotechnical and geophysical engineering applications including seismic site response analysis, liquefaction risk assessment and design of shallow and deep foundations. Moreover, the comparison of shear wave velocity between laboratory and in situ measurements has become a standard acceptance criterion for the assessment of sampling quality. Offshore in situ shear wave velocity testing is considerably more challenging than onshore, due to the difficulties in the correct deployment of the instrumentation as well as of the wave source, in absence of direct visibility of the ground level below water. This paper describes the methodology employed for offshore shear wave velocities (Vs) measurements in the harbour of Barcelona in September 2022. Medusa SDMT tests were performed in sea depths ranging between 15-17 m from a jackup and employing a drill rig to penetrate the probe down to 40 m below the seafloor. The paper includes examples of recorded S-wave seismograms, analyses of Vs repeatability for the same depth measurements and Vs profiles with depth. In the same test locations, carefully prepared specimens of undisturbed samples were tested after reconsolidation to the estimated in situ stress states in stress path triaxial cells with bender elements transducers. The obtained lab shear wave velocities were compared with the in situ values obtained with the Medusa SDMT tests to assess sample quality

Unusual vertical oscillations in sodium density and the formation of sporadic sodium layer over the Zhongshan station

Unusual vertical oscillations with some wave structures were observed in the sodium (Na) density layers (SLs) in Antarctica on 1 September 2019, by means of the lidar located at Zhongshan (69°S, 76°E). There was a clear vertical convection of the wavy sodium density layers which populated the region at an altitude of between ~90 and ~102 km producing the Sporadic/Sudden Sodium Layers (SSLs). The vertical oscillations had an average wavelength, average speed and period of ∼3.0‑4.5 km, ∼7.8 m/s and ∼7.3‑8.5 min, respectively. The possible cause of these vertical oscillations, as well as the mechanisms that could be behind the generation of these oscillations and wavy SSLs, were investigated. The Global Positioning System (GPS) satellite receiver located at Davis (68.6°S, 77.9°E), 116 km away from Zhongshan, was used to derive the Total Electron Content (TEC) perturbations in the region surrounding Zhongshan. SuperDARN HF radar at Zhongshan also showed some waves in the first 10 range gates (180‑800 km away), suggesting that the Traveling Ionospheric Disturbances (TIDs) were propagating in the ‑region. The cross‑correlation between GPS and lidar wave structures was computed. A good to strong correlation of –0.6‑–0.9 was found between waves observed by GPS and lidar. Additionally, a moderate correlation was found between the SuperDARN radar and lidar wave structures. The lidar neutral temperature showed upward Atmospheric Gravity Waves (AGWs), while SuperDARN and GPS showed the downward TIDs. Based on the polar cap (PC) index, TIDs could have been generated by Joule heating due to geomagnetic storm effects in the region. The estimated Richardson number values between 80 and 105 km at 16:00‑24:00 UT suggest that convective and dynamic instabilities could have generated the observed SSLs and AGWs. Vertical oscillation of the sodium density layers could have taken place because of waves breaking and interference from the downward TIDs and upward AGWs

Monitoring and Station Health of Türkiye – KOERI Stations and Their Contribution to AdriaArray Seismic Network

The Kandilli Observatory and Earthquake Research Institute (KOERI) has played a pivotal role in seismic monitoring in Türkiye since the late 19th century. This study highlights recent advances in the KOERI seismic network including the installation of new broadband and accelerometer stations, data management under the European Integrated Data Archive (EIDA) and contributions to the AdriaArray project. AdriaArray is a large-scale passive seismic experiment designed to improve the resolution of seismic imaging and geodynamic models across southeastern Europe by integrating data from a dense broadband seismic network. This initiative enables detailed investigations of crustal and mantle structure, anisotropy, and lithospheric deformation, offering new insights intothe complex interactions between the Eurasian, Adriatic and Anatolian plates. As part of this effort, three key stations (DOGC, CRLU and TEKI) were installed in the Thrace Basin, providing valuable data for analyzing regional seismicity and tectonic activity. The performance of these stations was assessed alongside seismicity trends before and after their installation. This work emphasizes KOERI’s role in advancing regional seismic monitoring capabilities and its notable contributions to global seismological research. Furthermore, the findings underscore the transformative impact of high-density seismic networks in improving the detection of microseismic events and refining our understanding of tectonic processes. These developments also highlight the critical role of crossborder collaboration and state-of-the-art instrumentation in mitigating earthquake risks and fostering global geoscientific progress

Cellular Nonlinear Network for fluid dynamics: towards geophysical flows modeling

This work proposes an application of Cellular Nonlinear Networks (CNNs) to fluid dynamics, implemented towards the application to geophysical flows. We revisit the CNN paradigm for the solution of Partial Differential Equations with a focus of some main physical properties of geophysical flows. We address numerical aspects of the obtained model, including the treatment of boundary conditions, stability and correctness of the results. This is done by applying our method to canonical testcases and comparing the results with accepted benchmark data and analytical solutions from the literature. The parallelizability of the method is also assessed by means of benchmarking tests on a multi-core processor. We validate the model by simulating classical geophysical flows. The results that we present show the capability of the model to reproduce typical velocity profiles of viscous flows, making it promising for applications that require the simulation of such materials

The ANTICS Large-N Seismic Deployment in Albania

Located within the active continental collision between Eurasia and the Adriatic microplate, Albania is an earthquake prone country with one of the highest seismic hazard in Europe. This came into evidence when the MW=6.4 Durrës earthquake hit the country in 2019, causing 51 fatalities and widespread damage to infrastructure. Despite this stark reminder, the seismotectonics of Albania remains poorly researched, holding many unknowns regarding active seismogenic faults and 3D velocity structure. In an attempt to fill-in this knowledge gap, we conceived the project ANTICS (AlbaniaN TectonIcs of Continental Subduction) to install a temporary network of 382 seismic stations and densely monitor the abundant seismic activity in central Albania. In this paper we introduce the project goals and seismic deployment, assessing data quality and extracting valuable lessons from such a complex large-N deployment. Finally, we present some preliminary results on the detected seismicity and a receiver function profile and expand on an outlook of the project and possible next steps in the area

Spatial data and GIS for the assessment of the environmental impact at Mount Etna

One of the fundamental tasks for environmental impact assessment and natural risk management is the accurate and updated cataloging of road infrastructures and buildings. This is particularly important in volcanic areas, in order to predict the range of damage and disruption, and therefore losses and reconstruction costs that could result from an eruption. GIS allows immediate access to spatial data with the ability to overlay location-based information for easy interpretation, providing a critical tool for assessing and mitigating risk from natural phenomena. In this work, we present an innovative GIS‑based system for the identification of the values exposed to volcanic eruptions at Mount Etna, which can be used in both the readiness and response phases to a volcanic emergency. We carried out a precision mapping of buildings and road infrastructures on the flanks of the Etna volcano, giving particular attention to the exposed sensitive buildings (such as schools, barracks, hospitals, etc.) and to the construction and roofing characteristics. The result is an informative and dynamic platform that offers new opportunities and challenges to decision makers for the definition of both long‑term strategies, such as territorial planning, and short‑term strategies, for the prediction of the impact of eruptions or for managing evacuations during volcanic emergencies

Can the polarization tagging of the ionogram trace deceive autoscaling methods? The Learmonth case

This paper focuses on the problem of invalid O/X polarization tagging of an ionogram and how this can affect ionogram autoscaling methods. To illustrate this problem, 623 ionograms recorded in March and April 2004 (days 080-105) by the digisonde 256 installed at Learmonth (22.3° S, 114.1° E) were considered. These ionograms, often characterized by very unreliable O/X polarization tagging of the echoes because of unresolved antenna issues, have been autoscaled by both ARTIST 4.2 and Autoscala. Results of comparisons between automatically and manually scaled foF2 data are shown for both programs, considering as acceptable an autoscaled value that lies within 0.5 MHz of the manual value. Autoscala values of foF2 agree with the manually-scaled values for ~99% of ionograms, while ARTIST values of foF2 agree with the manually-scaled values for ~75% of ionograms. While ARTIST was coded on the assumption of valid polarization tagging, the fact remains that it produces invalid results when equipment issues cause invalid tagging. Autoscaling procedures that do not use the polarization tagging will generally work better than ARTIST in such cases. However, these other procedures are susceptible to failure in other situations