Giorgio De Donno

Detection and imaging of piping sinkholes by integrated geophysical methods

Piping sinkholes may naturally develop in the case of a thick overburden overlying calcareous bedrock. Their detection and imaging is a challenging task for geophysical methods, not only because of the required resolution and depth of penetration, but also because major pitfalls may arise, in such geologically complex areas, from the speculative interpretation of geophysical anomalies as geological features. Data integration from different geophysical methods is essential to remove these interpretation ambiguities, caused by large near-surface gradients and heterogeneities in the soil properties, as well as by oscillations of the water table and anomalous water circulation. We present an investigation procedure consisting of the sequential application and integrated interpretation of Electrical Resistivity Tomography (ERT), Seismic Refraction Tomography (SRT) and Self Potential (SP) measurements for locating and monitoring piping sinkholes with application to a site in Central Italy. This approach is a compromise between resolution and cost-effectiveness, and it is designed to be economically affordable by the private end user. In complex geological scenarios, it is usually not possible to rate a single geophysical technique as superior to all the others in terms of resolution, cost-effectiveness and diagnostic capability. The independent information coming from the different geophysical methods is the key to removing interpretation ambiguity when evaluating the position and the development over time of the piping sinkholes. The application of the proposed investigation procedure allowed us to individuate a small area subject to the formation of a piping sinkhole. The geophysical results were confirmed about one year after the execution of the geophysical measurements, as the site exhibited surface evidence of a piping sinkhole, with the formation of a small pond filled with sulphurous water and gases coming from below.

2D tomographic inversion of complex resistivity data on cylindrical models

The resistive and capacitive response of a multiphase subsoil can be analysed by amplitude and phase models of the electrical complex resistivity. The main goal of this work is to extend the 2D transformed formulation used for electrical site investigations for cylindrical laboratory models, solving the complex resistivity forward problem starting from the Complete Electrode Model approach. This formulation is tested by a comparison with the full 3D solution and is proven to be stable and accurate. Inversion of complex resistivity data is achieved through a Matlab interface included in the EIDORS environment, with the addition of numerous new functions. Three synthetic examples are discussed, to understand the potential and limits of this approach in comparison with the 3D inversion. Laboratory experiments on a cylindrical laboratory model with a horizontal cross-section of 10 electrodes validated synthetic results. The model having a height of 1 m and a diameter of 500 mm is made by sand contaminated from the top by an engineered fluid with electrical properties similar to chlorinated solvents.

Tomographic inversion of time-domain resistivity and chargeability data for the investigation of landfills using a priori information

In this paper, we present a new code for the modelling and inversion of resistivity and chargeability data using a priori information to improve the accuracy of the reconstructed model for landfill. When a priori information is available in the study area, we can insert them by means of inequality constraints on the whole model or on a single layer or assigning weighting factors for enhancing anomalies elongated in the horizontal or vertical directions. However, when we have to face a multilayered scenario with numerous resistive to conductive transitions (the case of controlled landfills), the effective thickness of the layers can be biased. The presented code includes a model-tuning scheme, which is applied after the inversion of field data, where the inversion of the synthetic data is performed based on an initial guess, and the absolute difference between the field and synthetic inverted models is minimized. The reliability of the proposed approach has been supported in two real-world examples; we were able to identify an unauthorized landfill and to reconstruct the geometrical and physical layout of an old waste dump. The combined analysis of the resistivity and chargeability (normalised) models help us to remove ambiguity due to the presence of the waste mass. Nevertheless, the presence of certain layers can remain hidden without using a priori information, as demonstrated by a comparison of the constrained inversion with a standard inversion. The robustness of the above-cited method (using a priori information in combination with model tuning) has been validated with the cross-section from the construction plans, where the reconstructed model is in agreement with the original design.

3D complex resistivity tomography on cylindrical models using EIDORS

ABSTRACT Complex resistivity imaging is a relatively new geophysical technique, developed in the last few decades mainly for hydrogeological and environmental applications. The aim of this work is to present an EIDORS application of the 3D complex resistivity tomography on cylindrical laboratory models. EIDORS is an open‐source numerical environment developed with the aim of sharing data and promoting collaboration between groups working in these fields. In spite of being a well‐recognised software for forward modelling and inversion for medical tomographies, EIDORS still needs to be adapted for geophysical purposes. We discuss the role played by the mesh choice and the contact impedances on the accuracy of the finite‐element solution achieved by tetrahedral elements. When a 3D tomography is performed on a standard machine with limited local memory, the dual reconstruction can help to retain a sufficient accuracy without increasing the allocated memory. Although for medical applications on the human body a linear inversion can effectively represent the slight changes in resistivity magnitude, when a subsoil has to be investigated resistivity can vary substantially. Thus we develop an algorithm to add to the non‐linear inversion for complex resistivity data, through the integration of the EIDORS basic functions. The algorithm has been validated through four synthetic examples. The reconstructed models, having a growing degree of complexity, are similar to the true ones. We highlight the role played by phase and resolution to detect the anomalies. When the dipole length is enlarged and the embedded anomalies decrease in size, the reconstruction becomes more difficult. We show that EIDORS could act as a base code for tomographic inversion of frequency‐domain data (and also of time‐domain real‐valued data) for laboratory problems, because of its high flexibility and reliability reached by the forward and inversion routines.