On 28 October, Researcher Đặng Hoàng Duy successfully defended the doctoral thesis titled: “Analysis of High-Frequency Electromagnetic Data Attributes in Subsurface Object Investigation” supervised  by Assoc. Prof. Lê Văn Anh Cường – Head of the Department of Geophysics, Faculty of Physics – Engineering Physics, VNUHCM-University of Science.

The research focused on in-depth analysis of Ground Penetrating Radar (GPR) data attributes for investigating shallow subsurface objects. Following an overview of the development history, GPR technology applications, and related studies, the thesis presented the theoretical basis, data collection and processing procedures, and delved into key attribute analysis techniques, including: the maximum energy difference attribute, the phase attribute, and the wavelet attribute.

The study utilised computational tools and algorithms to model and simulate GPR data, followed by analysis and comparison of the theoretical model results with field surveys. Analyses from these actual data clarified both qualitative factors (such as determining the metallic properties of subsurface objects) and quantitative data.

The new results of the thesis demonstrate the successful application of these attributes: the Phase Attribute determines material properties (metallic/non-metallic) through the phase shift of the reflected wave compared to the incident/direct wave. The Energy Difference Attribute helps detect and delineate scattering locations that differ from the surrounding medium, providing a basis for accurately determining the object’s position and shape. The Wavelet Attribute, furthermore, allows for the detection of minimal differences in the object’s wave nature compared to the surrounding environment by altering the analysis frequency, thereby helping to model the object more clearly in both quantitative and qualitative terms. The thesis also shows that combining traditional processing (such as time migration, noise filtering) with attribute processing enhances the effectiveness of interpretation work.

Regarding practical applicability, the research provides a foundation for the effective application of automated and semi-automated GPR attribute analysis procedures, allowing for precise determination of subsurface objects. This methodology holds high value in mapping urban underground utilities and surveying geological structures, particularly offering effective operation capability in urban environments which typically have high levels of interference affecting measurement quality. The author also proposed future directions aimed at completing automated procedures and continuing research into other attributes for application to GPR data.