Targeting potential mineral deposits via uncertainty analysis of magnetic inversions

The demand for mineral resources has markedly increased during the energy transition. Efficiently exploring potential mineral deposits, however, remains a significant challenge, primarily due to the inherent uncertainty in locating these deposits. This study introduces an innovative workflow, aimed at analyzing the uncertainty of potential mineral resources during exploration. To be specific, we randomly sample user-defined parameters of mixed Lp norm magnetic inversions. We generate a variety of susceptibility models, each of which is characterized by unique spatial features. We calculate the statistical characteristics of susceptibility values obtained from rock samples. These statistical features serve as critical constraints for the probabilistic interpretation of the inverted susceptibility models. We applied our workflow to a field application for exploring boron resources in the east of Liaoning province, China. We generate probabilistic mineral resource models, which are consistent with the deployed drillholes. The results demonstrate a significant improvement in the reliability of targeting mineral resources, paving the way for more efficient mineral exploratory activities in the future.