Semi-automated {Facies} {Correlation} based on logging data for a uranium roll-front deposit: rules and method evaluation.

@inproceedings{Borde2026RM,
 abstract = {This work addresses a key challenge for uranium exploration and production in sedimentary basins: generating consistent stratigraphic correlations from drilling data to support the construction of reliable and interpretable 3D geological models. In uranium exploration and mining, large numbers of boreholes are drilled, although not all are systematically cored. However, downhole geophysical logs, particularly resistivity logs, provide valuable vertical information that can be used to identify sedimentary facies at different depths. Based on sedimentary rules, these facies can be correlated between boreholes to build coherent 2D stratigraphic sections for exploration and interpretation. The integration of these sections then enables the development of 3D geological models, which are essential for resource estimation and production capacity assessment. In this context, facies interpretation and correlations generated by WeCo were compared with manual interpretations produced by sedimentologists considering both resistivity logs and cores in some wells. The objective was to assess the consistency of the semi-automatic results, identify the parameters influencing the quality of the correlations, and evaluate the potential of the software in an industrial workflow. The results show that the integration of Continuous Wavelet Transform (CWT) based lithological interpretation with WeCo assisted stratigraphic correlation improves the consistency of semi-automatic correlations compared with conventional approaches. The multiscale workflow provides the most geologically coherent results by combining large-scale stratigraphic trends with higher-resolution lithological information. This study contributes to the progressive improvement of sedimentary correlation rules and supports the validation of semi-automated approaches for geological modeling for uranium deposits in an industrial setting.},
 author = {Borde, Gabin and McKee, Kelsey and Martz, Pierre and Caumon, Guillaume and Letellier, Loïs and Antoine, Christophe},
 booktitle = {2026 {RING} meeting},
 language = {en},
 pages = {215--235},
 publisher = {ASGA},
 title = {Semi-automated {Facies} {Correlation} based on logging data for a uranium roll-front deposit: rules and method evaluation.},
 year = {2026}
}