Development of an Economic Cost Model for Gold and Associated Minerals Using Economic Analysis and Artificial Intelligence Approach

Abstract

Limited accuracy due to complex geological processes, insufficient data granularity, and challenges in predicting market dynamics impact mineral forecast models. In order to develop a cost-based model for gold and related minerals in Birnin Gwari (Kaduna State) and Kagara (Niger State), this study is being carried out in Nigeria. The created concept aims to increase the profitability and economic viability of open-pit mines operated by craftsmen and mining investors. By maximizing mine life cycles and preventing the early closure of mining sites, this was intended to encourage the best recovery rates. This study used economic and artificial neural network (ANN) modeling methods to create a cost-based model for ten gold-associated minerals. The coefficient of correlation (R²), root mean square error (RSME), and variance accounting factor (VAF) were used to assess the created model's correctness. The model evaluator demonstrates that the proposed cost-based models are economically viable and the quantitative results are as presented in Equations (14-23). The cost-benefit connection between gold and the ten related minerals was also determined using a least-squares regression analysis. According to geochemical results, the average values of gold and related minerals in the study region range from 4.87 g/t of gold (Au), 1.501 g/t of copper (Cu), and 187.13 g/t of iron (Fe) in Birni Gwari to 2.29 g/t of gold (Au), 1.358 g/t of copper (Cu), and 173.75 g/t of iron (Fe) in Kagara. In Birnin Gwari, the equivalent financial estimations are N876,600 for Au, N60,040,000 for Cu, and N1,129,375 for Fe, and N5,780,000 for Au, N49,500 for Cu, and N363,060,000 for Fe in Kagara. The model's scope demonstrates that running a single mineral can result in low recovery rates and a loss of profit margin; thus, the model's application to all open pit mines is relevant as a reference for profit margin cash flow.