In this MineTED episode, Dr. Nasser Madani discusses "Estimation of Mineral Resources Using Geostatistics Methods." The conversation covers converting geological data into block models for mineralization. Challenges include algorithm selection and adapting to varying spatial continuity in different deposits. Geostatistical algorithms bridge geological models and computational complexities. Machine learning aids quick mineral identification and complex modeling. Integrating machine learning into mining operations with limited data poses challenges.

Watch on YouTube

Nasser Madani, an Associate Professor at Nazarbayev University's School of Mining and Geosciences in Kazakhstan. With expertise in stochastic modeling of geological domains, specializing in mineralization, alteration zones, estimation domains, and facies. Focuses on developing models and algorithms to address homogenous and zonified behaviors to quantify uncertainty in their layouts. Extends knowledge to continuous variables, applying linear and nonlinear Geostatistics to ore body modeling.

Connect with Nasser on LinkedIn