From Heterogeneous Borehole Data to City-Scale 3D Geological Modelling Supporting Seismic Response Studies for Northern Metropolis in Hong Kong
DOI:
https://doi.org/10.21467/proceedings.8.2.35Abstract
Complex geologic conditions in Hong Kong necessitate high-fidelity geological models to ensure safe infrastructure development and effective risk mitigation. While the region possesses a vast repository of geotechnical data, managing mix of many different data creates a significant challenge for data utilization. This study introduces a comprehensive workflow to address these challenges through the development of two Python-based automation tools: AGSGEOHKpy and PDFGEOHKpy. These tools facilitate rapid, uniform extraction of critical geotechnical parameters including stratigraphy, SPT-N values, undrained shear strength (Su), and groundwater level from heterogeneous datasets. To synthesize this extracted data into a coherent spatial model, a Python-based hybrid geo-interpolation framework was employed. This approach utilizes the Kriging Interpolation Method (KIM) to generate continuous surfaces for primary soil and weathered rock layers, while Inverse Distance Weighting (IDW) is applied to determine specific lithologies at unknown interpolated coordinates between these main geological boundaries. Leveraging this automated framework, a high-resolution 3D geological model was constructed based on a dataset of thousands of collected boreholes in Hong Kong island. The model has been rigorously validated against existing geological maps and cross-sections. Then, the proposed methodology has been applied for Northern Metropolis Hong Kong (NMHK). Beyond stratigraphic visualization, this paper demonstrates the model's capacity to support advanced engineering and hazard assessment applications. A 3D Shear Wave Velocity (Vs) model was derived to calculate fundamental site periods based on rockhead depth, providing essential data for seismic site-specific response analysis in Northern Metropolis. Furthermore, the enhanced precision of this geological modelling framework significantly improves design confidence for complex infrastructure projects.
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