Arithmetic Integration of GPR and Magnetic Data Based on Microwave Tomography (MWT) and Depth from EXtreme Points (DEXP)

In geophysics, it is common to employ multiple complementary geophysical exploration techniques to gather as much information as possible about the subsurface. In this framework, the concept of “data integration” emerges, referring to the combination of different datasets to extract more insights than those derivable from individual datasets alone, thereby enhancing information content and reducing interpretative ambiguities. While the goal of data integration is widely recognized, defining an optimal approach for the effective combination of different datasets remains an open research topic, strongly dependent on the acquired data and on the geophysical techniques considered.

In this work, we present a preliminary workflow for the integration of data from two main geophysical exploration techniques: Ground Penetrating Radar (GPR) and magnetic method. GPR is an active method sensitive to dielectric permittivity contrasts, while magnetic method is passive and sensitive to magnetic susceptibility contrasts. These two methods, despite being fundamentally different, are often used together in several contexts, enabling the detection and localization of buried targets through the analysis of electromagnetic and magnetic anomalies within the investigated domain.

Moreover, both methods benefit from advanced imaging techniques, such as Microwave Tomography (MWT) for GPR and Depth from EXtreme Points (DEXP) for magnetic data, which further enhance their potential in detecting and localizing anomalous bodies.

Specifically, the proposed workflow aims at the quantitative integration of GPR and magnetic data exploiting the results obtained from their respective MWT and DEXP imaging techniques, yielding a single composite result, which enhances interpretability and improves the characterization of anomalous targets in terms of morphology, position, and depth.

The workflow was validated through its application to simulated GPR and magnetic datasets for a common representative scenario, as well as to real datasets. Both simulated and real GPR and magnetic data were processed via MWT and DEXP, respectively, and subsequently their arithmetic integration was performed. The obtained results demonstrate the potential of the proposed workflow in obtaining a single result that outperforms the ones from individual methods, overcoming their limitations and yielding more accurate and detailed subsurface models.

Acknowledgments. This research has been founded by EU - Next Generation EU Mission 4, Component 2 - CUP B53C22002150006 - Project IR0000032 – ITINERIS - Italian Integrated Environmental Research Infrastructures System.