UFLI-Based Uranium Anomaly Layer Delineation and 3D Orebody Reconstruction of the Daying Uranium Deposit Within the Northern Ordos Basin, China

Read full text
Authors: Yulei Tan, Jianyu Huang, Liyuan Zhang, Laijun Lu, Baopeng Chen, Tongyuan Liang, Lin Pan
Cited by: 0
References: 55

Abstract

Sandstone uranium deposits exhibit stratabound mineralization and strong vertical heterogeneity in geological space, which complicates the identification of uranium anomaly layers and their integration into deposit-scale 3D models using borehole datasets. In this paper, we propose a UAPC Fourier layer identification (UFLI) method for uranium anomaly layer identification. The method is based on multi-log feature construction, random forest-based estimation of a depth continuous uranium anomaly probability curve (UAPC), and improved Fourier vertical variation analysis. We used 19 boreholes arranged on four exploration lines (ZKA-ZKD) of the Daying uranium deposit in the northern Ordos Basin (north central China), for the validation. The proposed UFLI method identified 51 uranium anomaly layers at a 5 m sampling interval, forming discrete vertical clusters within the drilled successions. The results indicate that anomalies are overwhelmingly concentrated in the Middle Jurassic Zhiluo Formation, particularly within the lower Zhiluo member, with an anomaly-bearing depth range of approximately 550–745 m. Comparison with known mineralization records shows that both industrial and ordinary mineralization intervals are captured within the anomaly layers. Then, based on inter-borehole continuity of anomaly layers, we reconstructed five uranium orebodies (orebodies 1–5) and describe their distribution characteristics. The proposed method provides a technical means for subsurface visualization and exploration targeting in sandstone uranium systems.

Fields of Study & Subjects

Geochemistry and Geologic Mapping Geological Modeling and Analysis Geoscience and Mining Technology

Publication details

Journal / source
Geosciences
Volume
16
Issue
3
Pages
111–111
Publication date
9 March 2026
Language
EN