Intelligent identification of lithology and adverse geology: A state-of-the-art review

作者：Zhenhao Xu, Tengfei Yu, Shucai Li, Shucai Li, Peng Lin, Wen Ma, Tao Han, Shan Li, Shan Li · 发表于：Smart Underground Engineering · 年份：2025 · DOI：10.1016/j.sue.2025.04.001 · 被引用次数：14 · 研究领域：Hydrocarbon exploration and reservoir analysis、Geochemistry and Geologic Mapping、Mineral Processing and Grinding

• The high-precision intelligent lithology identification methods have been developed. • Comprehensive identification of adverse geology form and nature has been achieved. • New theories and methods have been proposed for the quantitative inversion of elements and minerals. • A dual-driven method for rapid, multi-scale identification of adverse geology has been constructed. • Multi-source data fusion is the future direction for lithology and adverse geology identification. The accurate and timely identification of lithology and adverse geology is crucial for the safe and efficient construction of tunnels. However, traditional methods for lithology and adverse geology identification rely excessively on the experience and accumulated knowledge of geologists, making them highly subjective and prone to misjudgement and omission. This study aims to introduce the latest advancements in lithology and adverse geology identification. First, we present an innovative high-precision method for the intelligent identification of lithology based on “pure image,” “infrared spectral,” and “image and spectral fusion” analyses. Second, we propose methods of adverse geology identification, including “element and mineral anomaly analysis,” “geological and geophysical joint inversion,” and “multi-source data fusion of borehole information,” which realize comprehensive identification of the location, shape, scale, property, and type of adverse geology ahead of a tunnel working face. Finally, we pre...