NSG2023 29th European Meeting of Environmental and Engineering Geophysics

The advantages of geophysical imaging are widely appreciated by the archaeological community. Geophysics allows for the non-invasive detection and characterisation of archaeological targets, and also serves as a means of conveying the archaeological significance of a site to an interested audience. Survey data can make effective contributions to heritage management, whether they are used to plan excavations, restrict public access over sensitive sites, or presented as part of exhibitions. However, unlike excavated artefacts, which may be sufficiently robust to be handled, the presentation of geophysical data is entirely visual and thus risks excluding exhibition visitors — specifically those with a visual impairment and/or neurodiverse condition. Museum services are increasingly invested in improving EDI (Equity, Diversity, Inclusivity) practice, but the appreciation of geophysical data risks being overlooked. In this abstract, we review the geophysical, technical and functional considerations in converting ground-penetrating radar (GPR) timeslices into tactile surfaces, drawing on experience from neuroscience and design fields. The data we consider originate from a multi-platform archaeological survey over industrial foundations. We highlight the value of our tactile resources for widening participation in heritage communication, but also for any sector where public understanding of geoscience data is of critical importance.

Converted-wave (S-wave) statics are a crucial component of processing and imaging PS-wave data. We introduce a new method to calculate S-wave statics via a PS-receiver-stack image. Before stacking a PS dataset to a PS-receiver-stack image, source-side P-wave statics and common-conversion-point normal-moveout (CCP-NMO) correction are applied to the PS dataset. S-wave (receiver-side) statics therefore are the only outstanding statics on this PS-receiver-stack image. The PP dataset, corresponding to the PS dataset, is processed in a similar manner: before stacking it to a PP-receiver-stack image, NMO correction along with all available statics, both source-side and receiver-side, are applied. A target event on the PP-receiver-stack image is further picked out before it is converted to a PS-guidance structure via a-priori PP-to-PS velocity conversion ratios. Due to the fact that the corresponding target PS event on the PS-receiver-stack image is only with the correction of source-side (P-wave) statics, time differences exist between this target PS event and the PS-guidance structure, which are the result of the missing S-wave statics. Consequently, S-wave statics can be retrieved via aligning the PS target event on the PS-receiver-stack image to the PS-guidance structure. The success of our method is demonstrated with a demo on a challenging field dataset.

In recent years, global concerns about greenhouse gas emissions have stimulated considerable interest in carbon capture and storage (CCS) as a climate change mitigation option. A significant issue for storage security is the geomechanical response of the reservoir. For instance, there are injection-induced stress, strain, deformations, and potential microseismic events resulting from changes in reservoir pressure and temperature. Unwanted unelastic mechanical changes might reduce sequestration efficiency and cause concerns in the local community. Accurate time-lapse surveys can be used to image changes in seismic velocity induced by geomechanical deformation. Within the ACT-funded DigiMon project, a seismic field test was planned and carried out in September 2021 at the CO2 field lab in Svelvik near Drammen in Norway. At the Svelvik test-site, an injection well and four observation wells with a depth of 100 m are installed. The observation wells are positioned at the corners of a rhombus around the injection well. The experiment was designed to monitor the propagation of CO2 during the injection using high-resolution P-wave seismic tomography with conventional receivers (hydrophones) and the installed DAS (Distributed Acoustic Sensing) cables. Furthermore, S-wave sources were used to generate SH- and SV-waves during different stages of injection.

Methana Volcano-Peninsula (MVP), NE Peloponnesus, Greece, has geothermal potential and the detection of its deep structure is of great interest. Geophysical survey consisting old aeromagnetic data, new gravity and magnetic land data acquisition and their respective map analysis and then their 3D inversion have shown the full picture of the subsurface with the volcanic presence, the faults that control both volcanic as well as geothermal activity, all coinciding with the geological analysis, with the resulting 3D models after inversion showing aerial and depth extent of all interesting features but most important indicating where is the most promising area for the geothermal exploratory borehole.

Using an on-site generator as a calibration source, we verify the orientation of an array of five 3C geophones through a machine-learning analysis. Adjacent to a melting glacier, the geophone orientation is critical for determining conclusively whether hundreds of small seismic events originate within the glacier to the northwest or due to rockfalls nearby in the southeast.

In this paper, we implemented the Levenberg-Marquardt (LM) and very fast simulated annealing (VFSA) algorithms to recover the IP effect from central loop transient electromagnetic (TEM) data. To incorporate the IP effect into the TEM data, we used the Cole-Cole (CC), maximum phase angle (MPA), maximum imaginary conductivity (MIC) and Jeffrey transform of chargeability. As a conventional approach in the inversion to reduce the scale effect and assign a positive value to the updated model parameters, we took a natural logarithm of the model parameters in all of the parametrization models and the normalized chargeability in Jeffrey transform. Furthermore, we used the area sine hyperbolic transformation of data to control the scale effect of the data in LM inversion. The result of inversion indicates that inversion of CC, Jeffrey transformed CC and MPA parameters form TEM data using LM algorithm is convincing enough, but the inversion of MIC parameters leads to a premature convergence.

Furthermore, with the CC parametrization of IP effect, the model parameter can be better recovered using VFSA algorithm. However, retrieving the MPA parameters using this algorithm is not successful. Additionally, when the Jeffrey transform is used, the IP parameters cannot be accurately recovered using the VFSA.

SGPR is a next-generation solution. Due to the low emission of electromagnetic waves, it meets the stringent environmental EMC standards. It is a high-speed device that automatically and effectively recognizes subsurface structures. It penetrates ground deeper than conventional GPRs and it has much better spatial resolution.

Thanks to the proprietary cloud software with 3D visualisation and data integration with other systems, the device meets the expectations of a vast audience. SGPR as an innovative solution offers enormous possibilities of application, ranging from the recognition and analysis of geological structures to complex construction and engineering infrastructure.

This is a pioneering GPR study to map submerged archaeological sites in the Amazon region. The GPR preliminary results for the Jenipapo site are presented in this resume. Jenipapo site is located on the Turiaçu River, Maranhão State, NE of Brazil. The region is known as Maranhense wetland where evidences of Amazonian indigenous villages from the pre-colonial period were found. The villages were lakeside dwellings supported by wooden pillars, corresponding to prehistoric stilt houses (Estearias). The objectives of this research are to refine the Estearias location and guide the search for archaeological artifacts. The results of the GPR profiles using 270 MHz showed the river bottom reflection and several diffraction hyperbolas suspended over the river bottom that are probably related to the top of the wooden pillars that supported the pre-colonial indigenous villages. This preliminary result is promising and can help to find archaeological materials.

The cave of Alistrati, is located in the Prefecture of Serres, Northern Greece near the foothills of Mount Menoikio, in the area of Petroto. This area is structured by crystalline limestones, where the development of a complex and multilevel karst system is favored. An extensive geomorphological survey was carried out for the accurate mapping of the karst surface above the cave, using UAS. For the investigation of a possible lateral extension of the existing karstic conduit, a detailed surface geophysical investigation was carried out. More specifically, three geophysical techniques were implemented: a) the Electrical Resistivity Tomography (ERT), b) the Ground Penetrating Radar (GPR) technique and c) the Very-Low Frequency (VLF) method. These 13 lines of the three geophysical techniques are fully matched at 4 locations and were join-interpreted, yielding remarkable findings. The comparative results of the above geophysical techniques, as well as their 3D presentation, highlight similar geophysical anomalies, evaluated as different types of karst system structures. Therefore, the combined geophysical survey has indicated the existence and interconnection of the first two karst levels of the area, up to a depth of 50m, as well as the possible extension of the Alistrati karstic conduit to the northeast.

Radio-Magnetotelluric (RMT) method is based on measurements of the electromagnetic (EM) field using military and civilian radio transmitters broadcasting in a frequency range between 10 to 1000 kHz as the source. In order to reach to higher signal to noise ratio and a deeper penetration depth, CSRMT measurements are performed using a controlled-source in a wider frequency range of 1 to 1000 kHz.

We accomplished a dense RMT and CSRMT survey over a waste-site in Cologne, Germany. Two perpendicular transmitters were set-up to obtain the full impedance tensor and the tipper elements. The data were processed and the corresponding apparent resistivity, phase and tipper were calculated. Here, we present and discuss the 2D and 3D inversion of the computed transfer functions.

In general, we image a high conductive waste body extending to a maximum depth of 15 m. The waste body indicates an internal structuring and is well confined to the former pit area. Below the waste, sandy gravel is deposited. Outside the waste the subsurface is highly resistive.

The results, are in a good agreement with former DCR results that are obtained from the same region indicating the reliability of the data acquisition, processing and inversion.