A Case Study of Quantitative Integration of Geophysical and Geotechnical Data for Site Characterization

Summary Site characterization in industries such as energy, construction, transportation, and environmental engineering requires an accurate geotechnical model of the subsurface. This model provides crucial information on the dynamic properties of soil and rock, which is essential for making operational decisions and managing project risks. An accurate description of the subsurface can be obtained through traditional geophysical methods like Multichannel Analysis of Surface Waves and Ambient Noise Tomography. However, these methods have limitations, such as the lack of real-time field interpretations and the inability to directly provide a usable ground model for engineers. A new software platform has been developed to overcome these challenges through the combination and optimization of existing technologies like Real-Time Pre-Scan, Ambient Noise Tomography, and Artificial Intelligence for Ground Information Models. This new approach improves the accuracy and efficiency of geotechnical site characterization, bridging the gap between geophysical and geotechnical domains. A case study has shown the effectiveness of the platform, leading to safer and more efficient construction practices.