Possibility of Monte Carlo simulation for predicting radioactivity in the Baghak, NE Iran

Abstract

Uranium deposits are found in various geological environments; therefore, these exist in almost all geological phases: in high degree of metamorphic, metasomatic, Metamorphism, Surficial and Volcanic to Sedimentary perimeters. In this study, the amount of uranium in the Baghak mine (as a case study) was predicted using piecewise regression and Monte Carlo simulation at a 90% confidence level. To this end, 151 geochemical samples from the study area were analyzed, with rare earth elements, thorium, and yttrium selected as independent parameters due to their highest correlation with uranium. An equation was derived for estimating uranium levels, showing a high correlation (86%) with actual data. Based on the final model, 2,200 random data points for uranium were generated, with the mean differing by only 0.1 (logarithmic unit of concentration) from actual values. This indicates the model’s high accuracy in simulating real values. The simulated values closely matched actual values based on the density function, confirming the model’s validity. In this area, the confidence interval for uranium is from 1.8 to 2.6 based on logarithmic calculations. Finally, the independent parameters were prioritized based on their impact on predicting uranium levels. This research could be considered a practical tool for assessing and predicting uranium concentrations in various regions and could aid in improving mineral resource management.