Python-Based Visualization and Characterization of Subsurface Profile for a Long-Distance Subway Alignment in Manila

Subsurface investigations for long-distance route projects such as tunnels produce substantial data from multiple boreholes and various tests. These datasets require extensive processing and analysis to provide reliable subsurface profiles for further design and construction of tunnel structures and subway stations. In order to ensure that the data are understandable and actionable for the end user, an effective data communication is crucial. In this study, a Python code was developed to quickly visualize the borehole and laboratory data versus depth along the survey line, including seismic velocities VP and VS, and VP/VS, as well as various available geotechnical data. Two common methods to contour data for visualization available in Matplotlib, i.e., tricontourf() and contourf(), were employed. As a result, this study was able to generate value-added subsurface profiles to supplement the existing conventional geotechnical soil profile for a subway alignment in Manila, the Philippines. Visualization of geotechnical and geophysical properties revealed zones of highly fractured materials and/or weak zones along the study subway line project, which may be critical during excavation works and construction. In this paper, some potential sources of uncertainties from the developed Python codes are also discussed for further improvement in future.