Multi-source data integration and multi-scale modeling framework for progressive prediction of complex geological interfaces in tunneling

Abstract

A reliable geological model plays a fundamental role in the efficiency and safety of mountain tunnel construction. However, regional models based on limited survey data represent macroscopic geological environments but not detailed internal geological characteristics, especially at tunnel portals with complex geological conditions. This paper presents a comprehensive methodological framework for refined modeling of the tunnel surrounding rock and subsequent mechanics analysis, with a particular focus on natural space distortion of hard-soft rock interfaces at tunnel portals. The progressive prediction of geological structures is developed considering multi-source data derived from the tunnel survey and excavation stages. To improve the accuracy of the models, a novel modeling method is proposed to integrate multi-source and multi-scale data based on data extraction and potential field interpolation. Finally, a regional-scale model and an engineering-scale model are built, providing a clear insight into geological phenomena and supporting numerical calculation. In addition, the proposed framework is applied to a case study, the Long-tou mountain tunnel project in Guangzhou, China, where the dominant rock type is granite. The results show that the data integration and modeling methods effectively improve model structure refinement. The improved model's calculation deviation is reduced by about 10% to 20% in the mechanical analysis. This study contributes to revealing the complex geological environment with singular interfaces and promoting the safety and performance of mountain tunneling.

Keywords

• Mountain tunnel
• Geological modeling
• Multi-source data
• Progressive prediction
• Tunnel portals