A new integrated 3D modeling method based on multisource heterogeneous geological data and its application

Abstract

With continuous advancement in geological studies, three-dimensional (3D) geological modeling technology based on big data and artificial intelligence (AI) has become a prominent focus in the interdisciplinary field of earth and information sciences. Through the analysis and comparison of existing 3D modeling methods, this study introduces a high-precision 3D geological modeling approach. The new method leverages advanced computing technologies, including multisource heterogeneous data processing, integrated model databases, seamless splicing of local models, and cluster analysis. Furthermore, it enables unified 3D visualization of subsurface and surface conditions, providing new insights into disaster prevention, mitigation, and intelligent mineral exploration. To validate its practicality, this study conducts 3D geological modeling of the X area within the Sichuan Basin, China. The data sources include remote sensing images, geological maps, geophysical data, borehole data, and X-ray fluorescence (XRF) spectroscopy data. Preliminary exploration in the X area has successfully identified new mineralization belts, verifying the feasibility and effectiveness of the new 3D geological modeling method that integrates big data processing and intelligent techniques.

Keywords

Big data / Artificial intelligence / Geological modeling / Multisource heterogeneous data / Intelligent mineral exploration / Remote sensing images / Geological maps / Geophysical data / 3D visualization

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