Journal of

GEOsciences

  (Formerly Journal of the Czech Geological Society)

Original paper

Oğuz Turunç, Mehmet Demirbilek

Three-dimensional geological modelling, geostatistical evaluation, and resource estimation of the Şamlı Iron Ore Deposit, Balıkesir, Türkiye

Journal of Geosciences, volume 70 (2025), issue 4, 229 - 252

DOI: http://doi.org/10.3190/jgeosci.0041.25

The studies on mineral resources modelling and reserve estimation require a rigorous methodological framework and a multidisciplinary analytical infrastructure to ensure that quantitative assessment results accurately reflect geological reality and are presented reliably. The uncertainties inherent in reserve estimation, production planning, and economic valuation processes necessitate the characterization of project risks based on scientific facts. In this context, our study aims to evaluate the resource potential of the Şamlı Iron Ore Deposit through three-dimensional geological modelling and geostatistical methods. The studied ore deposit, located in the north of Balıkesir, western Turkey, exhibits skarn/iron oxide copper-gold (IOCG) type mineralization. The study integrated data from 161 diamond core drillholes, totaling 16,283.40 m, using Leapfrog Geo, Snowden Supervisor, and Datamine Studio RM software. Four main mineralization zones were defined, and solid models were constructed and integrated with block modelling. Geostatistical analyses revealed that iron (Fe) grade exhibits moderate spatial continuity with an influence range of 150 meters and a nugget effect accounting for 8 % of the total structural variance. According to the Ordinary Kriging method with optimized parameters, the estimated resource potential of the deposit, at a cut-off grade of 28 % Fe, was determined to be 2,031,657 tons with an average grade of 48 % Fe. The high reconciliation level (92.3 %) between the predicted grades of mined blocks and the actual production data confirms the operational accuracy of the model. These results reveal that the adopted methodology provides a reliable framework for evaluating iron deposits in similar geological settings and can significantly mitigate project risks.