PHOSPHATE RESERVE ASSESSMENT USING NUMERICAL SIMULATION: CASE STUDY OF THE KEF ESSENNOUN DEPOSIT, ALGERIA

Abstract

The beneficiation of mineral resources plays a critical role in strengthening national economies, improving living standards, and advancing sustainable development. This study focuses on the sustainable exploitation of phosphate reserves in the Kef Essennoun deposit, located in Bir El Ater, Tebessa. Through the integration of geological data, drilling logs, and structural analysis, we examine mineral distribution, alteration zones, and lithological characteristics to delineate high-grade zones for targeted extraction. Our research emphasizes the transformative impact of data science in modern mining operations, showcasing how advanced analytics, including machine learning and predictive modeling, can optimize resource assessment and management. These techniques allow for accurate evaluation of ore grade variability, deposit geometry, and geotechnical conditions—key parameters for effective decision-making. By developing a spatial model of grade distribution within the deposit, this study provides actionable insights for improving extraction efficiency while reducing environmental impact. The integration of traditional geological methods with innovative data-driven tools fosters a holistic framework for maximizing resource recovery. Moreover, the findings underscore the value of interdisciplinary collaboration between geoscientists and data scientists in modernizing exploration and beneficiation strategies.

This study develops a spatial model of grade distributions within the deposit, enabling stakeholders to optimize extraction parameters. Combining geological expertise with advanced data analytics, we introduce a framework to enhance resource recovery while reducing environmental impact. The results demonstrate how interdisciplinary collaboration can transform mining practices, balancing economic and ecological sustainability. By offering a replicable approach, this research advances sustainable resource management, providing a scalable model for global phosphate deposits.