DEVELOPMENTS IN E&EM GEOPHYSICS:JOINT INVERSION, TIME-SERIES ANALYSIS AND SYSTEM CALIBRATION

The research presented in this Ph.D. thesis stemmed from the largest Airborne Electromagnetic (AEM) campaign ever conducted in Italy between 2021 and 2023, and from the specific challenges arising from this project. The campaign aimed to investigate the geological and hydrogeological architecture of a region in northern Italy at multiple observational scales—large, medium, and high-detail—to support long-term hydro-management strategies. The first expected outcome of the Ph.D. was the establishment of the HydroGeosITe within the AEM survey area. This site was conceived as a reference and bridge between the large-scale geophysical models derived from the airborne campaign and their lithostratigraphic interpretation. At the same time, the HydroGeosITe was designed to serve as a calibration site for AEM systems, supporting future campaigns. Accordingly, a key research objective was to advance the state of the art in AEM calibration procedures, setting a new standard for Italy. At the HydroGeosITe, an extremely dense E&EM dataset was acquired using multiple systems to ensure broad sensitivity and spectral coverage. The first technical development has been a novel joint inversion approach for E&EM data, applied for the first time to model the HydroGeosITe, retrieving subsoil models with unprecedented resolution validated with borehole comparison. This joint approach enabled a new level of translation from geophysical to geological information, supported at the HydroGeosITe also by extending the high-resolution 2D joint models into a full 3D volume. In the second part of the thesis, the research shifted toward temporal analysis of E&EM data, addressing both specific challenges in time-lapse analysis and leveraging those advancements to improve EM calibration procedures. In this context, seasonal temperature effects were first examined through a long-term monitoring survey using galvanic data. Here, temperature oscillations masked the target anomalies, rendering the data unusable. To overcome this, a novel inversion scheme was developed to filter out temperature effects by inverting for ground thermal diffusivity—without requiring in-situ temperature measurements at the time of acquisition. Since similar seasonal effects were found to influence subsurface models during EM instrument calibrations—particularly when calibrations are performed in different seasons—a dedicated study was conducted to investigate the impact of temperature on EM data, highlighting the risk of misinterpreting thermal variations as instrument-related differences. Still within temporal analysis, the study continued with an AEM time-lapse dataset from southern Australia. The dataset was modelled to investigate the hydrogeological evolution of a hypersaline floodplain and its freshwater recharge at basin scale. A dedicated time-lapse inversion framework was developed specifically for airborne EM data. Beyond its standalone results, this multitemporal modelling scheme provides a tool for future AEM campaigns opening the way to time-lapse acquisitions. Finally, the last chapter converges into a discussion on how the research results presented should be used for reference and calibration purposes. First, the analysis of temperature effects is further deepened—showing they can have a greater impact than some commonly prioritized transfer function parameters. Then, the application of the full joint workflow, from acquisition to modelling, to the CSIRO calibration line in Australia demonstrates the value of high-resolution sites as references for large-scale geophysical studies.