  Given the challenges in data acquisition and modeling at the stage of
detailed exploration, it is difficult to develop a prospectivity model,
particularly for disseminated ore deposits. Recently, the weights of evidence
(WofE) method has demonstrated a high efficiency for modeling such deposits. In
this study, we propose a framework for creating a three-dimensional (3D)
weights of evidence-based prospectivity model of the Nochoun porphyry Cu
deposit in the Urmia-Dokhtar magmatic arc of Iran. The input data include
qualitative geological and quantitative geochemical information obtained from
boreholes and field observations. We combine ordinary and fuzzy weights of
evidence for integrating qualitative and quantitative exploration criteria in a
3D space constrained by a metallogenic model of the study area for identifying
a deep-seated ore body. Ordinary weights of evidence are determined for
geological data, including lithology, alteration, rock type, and structure.
Moreover, we determine the fuzzy weight of evidence for each class of
continuous geochemical models created based on Fe, Mo, and Zn concentration
values derived from boreholes. We integrate the input evidential models using
WofE and create two prospectivity models (i.e., posterior and studentized
posterior probability). We also determine anomalous voxels in the probability
models using concentration-volume fractal models and validate them using
prediction-volume plots. The modeling results indicate that the studentized
posterior probability model is more efficient in identifying voxels
representing copper mineralized rock volumes. We provide open source software
for the proposed framework which can be used for exploring deep-seated ore
bodies in other regions.
