Geostatistics originated in the 1950s and 1960s as an evolution of classical statistics to address prediction problems in mining, forestry, and meteorology. In natural systems, such as mineral deposits, neighbouring measurement points tend to have similar values rather than random fluctuations. Geostatistics provides a more precise mathematical framework for describing this relationship compared to traditional methods, resulting in improved predictions for individual points, as well as areas and volumes.

By the late 1980s, many of the methods currently in use had been developed or were proposed in theory, although some required advances in computer technology to fully realize their potential. In the 1990s, geostatistical methods became more widely adopted in the mining industry.

Today, geostatistics is widely used in fields such as mining, environmental monitoring, agriculture, spatial statistics (GIS), and data science. Linear models are commonly employed, and advances in computer technology have made it possible to use simulations and multiple scenario options more frequently.

Looking forward, this panel discussion will explore current developments in geostatistics and how they can improve the accuracy of predictions and risk evaluations.