What geostatistical parameter primarily quantifies the spatial correlation of ore grades within a deposit?

The geostatistical parameter that primarily quantifies the spatial correlation of ore grades within a deposit is the variogram. The variogram measures the average dissimilarity between data values separated by a specific distance and direction. It's a crucial tool in understanding how ore grades change as you move away from a sample location. It examines the difference in ore grade values at varying distances. Specifically, the variogram calculates half the average squared difference between the values of the variable (ore grade) at locations separated by a vector h. This vector h represents both the distance and direction between the sample points. The variogram is typically plotted as a graph showing the semi-variance (half the average squared difference) on the y-axis against the distance (lag) h on the x-axis. Key features of a variogram include the nugget, sill, and range. The nugget effect represents the variance at zero distance (the y-intercept), indicating measurement error or micro-scale variability. The sill is the maximum semi-variance value that the variogram reaches, representing the total variance of the data. The range is the distance at which the variogram reaches the sill, indicating the distance beyond which data values are no longer spatially correlated. A shorter range implies that ore grades change rapidly over short distances, while a longer range indicates that ore grades are correlated over larger distances. Understanding the variogram is essential for geostatistical estimation techniques like kriging, which uses the spatial correlation information to predict ore grades at unsampled locations.