Advancing geological modelling and geodata management: a web-based system with AI assessment in Singapore
Haoqing Yang, Jian Chu, Shifan Wu, Xing Zhu, Xiaohui Qi, Kiefer Chiam
Abstract
This paper outlines the development and deployment of the Geodata Modelling and Management System (GEM2S) in Singapore. GEM2S offers a sophisticated web-based platform for visualising and interacting with 3D geological models of Singapore. Beyond basic visualisation and interaction, GEM2S provides advanced features for geodata management, including the functionality to upload new borehole data with AI assessment and to integrate geophysical results. The paper begins by elucidating the data processing procedures, which involve extracting data from electronic site investigation records. Additionally, common data errors for cleaning and validation purposes are summarised. Subsequently, the paper presents the 3D geological modelling process and results. The architecture of the web-GIS geodata management system is detailed, outlining the data flow and functions for interactive queries. Furthermore, the paper investigates two AI-based prototypes for quality assessment of newly acquired borehole data. Incorporating virtual boreholes generated from the geophysics effectively enhances the quality of the resulting geological model. GEM2S can serve as a comprehensive and user-friendly platform, making it a valuable system for underground project design and a foundational database for future subsurface planning in Singapore.