Three-dimensional weights of evidence-based prospectivity modeling: A case study of the Baixiangshan mining area, Ningwu Basin, Middle and Lower Yangtze Metallogenic Belt, China

Abstract

This study uses geological data for the Baixiangshan iron deposit within the Ningwu Basin of the Middle and Lower Yangtze Metallogenic Belt, China, to create a 3D prospectivity model that defines prospective areas for future exploration for iron mineralization in the study area. The first stage of this modeling was to define geological and mineral deposit models for the Baixiangshan iron deposit, before determining quantitative exploration criteria using 3D spatial analysis; these criteria were then either split into prospective (e.g., positive magnetic anomalies) and unprospective areas using a threshold value (prospective areas have anomalies >980nT) or were buffered to determine the spatial relationship between these criteria (the locations of faults, the bottom contact of the Lower Huangmaqing Formation, the top contact of the dioritic intrusion, and the location of blocks uplifted during intrusion) and mineralization; the prospective parts of these datasets were then in turn used to define prospective and unprospective areas on binary predictive maps. These binary predictive maps were then combined to create a weights of evidence-based 3D prospectivity model. This model highlights five highly prospective areas >100m outside of areas of known mineralization that are favorable for exploration in the Baixiangshan mining area, all of which should be considered as high priority targets for future exploration. In addition, the modeling presented here indicates that an approach combining legacy geological data with 3D spatial analysis and weights of evidence modeling can identify the controls on mineralization within known orebodies. This knowledge can then be used to more effectively target areas for future mineral exploration.