Towards a Quantitative Integration of Geophysical and Geotechnical Data for Site Characterization: Case Studies

A geotechnical model of the subsurface is essential for site characterization in industries like energy, construction, transportations and environmental engineering. It provides crucial information on soil and rock dynamic properties that are needed to make operational decisions and manage the project risks. Traditional methods like Multichannel Analysis of Surface Waves and Ambient Noise Tomography have limitations, including lack of real-time interpretations in the field, and they do not directly provide a ground model usable by engineers.

To address these challenges, a new software platform combining and optimizing existing technologies such as Real-Time Pre-Scan, Ambient Noise Tomography, and Artificial Intelligence for Ground Information Model has been developed.

This approach enhances the accuracy and efficiency of geotechnical site characterization, bridging the gap between geophysical and geotechnical domains.

A case study in Qatar demonstrated its effectiveness, paving the way for safer and more efficient construction practices.