Geostatistics with Data of Different Support Applied to Mining Engineering

Geostatistics with Data of Different Support Applied to Mining Engineering by Marcel Antonio Arcari Bassani and João Felipe Coimbra Leite Costa is a practical and advanced guide tailored for mining professionals, engineers, and students. This book addresses a critical challenge in resource estimation: how to effectively integrate and model geological data collected at varying sample supports—such as different drillhole lengths or data resolutions—using geostatistical methods.

Focusing on real-world mining applications, the authors provide a clear and concise approach to using kriging and simulation techniques, such as Direct Sequential Simulation (DSS) and Sequential Indicator Simulation (SIS), with data of different support. The content is structured around practical case studies that reflect the complexity of mineral deposits, including continuous and categorical variables.

Key topics include:

• Kriging with point-to-block and block-to-block covariances

• Variogram regularization and deconvolution techniques

• Direct Sequential Simulation with support-consistent conditioning

• Geological uncertainty analysis using categorical data

• Integration of interpreted block models and drillhole samples

Ideal for mining geologists, resource modelers, and graduate students, this book offers actionable tools and insights to improve the accuracy of grade models, manage geological uncertainty, and support data-informed decision-making in mining operations.