Blog

New blog posts on challenges and solutions in geostatistical and geometallurgical modeling every month

Geostatistics with Nonlinear Variables

Clayton Deutsch


Many rock properties like mass fractions, volume fractions, thickness, and position average linearly. For rock properties that average nonlinearly, one rock type would have more influence on the effective property. This is common with variables such as recovery and throughput. In special circumstances, the effective property can go outside the range of the two pure components. This would depend on specific chemical reactions or increased efficiency of a mixture relative to a pure component, for example, performance of a semi-autogenous grinding (SAG) mill.


Resource Calculation with Incomplete Information

Clayton Deutsch


In most cases, mining will benefit from significantly more data in the future than available at the time of resource calculation. There may be one hundred times more data at the time of mining from blast hole samples or dedicated grade control drilling. The uncertainty will be greatly reduced. The best estimate calculated with relatively widely spaced exploration drill holes will not represent what can be achieved at the time of mining. This is referred to as the Information Effect and is managed in different ways...


Trends in Geostatistics

Clayton Deutsch


A trend in geostatistics could be a general tendency in the direction industry is taking, such as towards automation. A trend in geostatistics is also a non-stationary or locally-varying mean in a regionalized variable, particularly for a continuous variable. This kind of trend is common and must be considered in probabilistic resource modeling; otherwise, high values are smeared into volumes they do not belong and low values dilute high valued volumes. Two questions arise: (1) how to model the trend? and (2) how to model with a trend?


Resource Modeling as an Essential Service

Clayton Deutsch


Mining provides critical resources and products that society needs, but what of resource modeling within the mining sector? A critical analysis of what we do in resource modeling suggests that the cost of a precise and accurate quantification of resource uncertainty is modest with appropriate software and trained professionals. The benefits are far greater than the cost: raw data are turned into support information for important short- and long-term decisions...


The Gaussian Distribution in Geostatistics

Clayton Deutsch


Gaussian algorithms have infected virtually all corners of geostatistics: radial basis functions (RBF) for interpolation and implicit modeling, hierarchical truncated pluriGaussian (HTPG) for categorical variable modeling, detrending non-stationary variables with a Gaussian Mixture Model (GMM), projection pursuit multivariate transformation (PPMT) for multivariate modeling, and simulating regionalized variables based on turning bands, sequential or spectral algorithms...


Public Disclosure of Probabilistic Resource Estimates

Clayton Deutsch


The state of nature is uncertain. Geological variability at all scales and sparse sampling make resource uncertainty an inevitable reality for mining companies and the concerned public. The workflow for probabilistic resource estimation is established, providing accurate and precise estimates of uncertainty in local and global resources...


Probabilistic Resource Estimation

Clayton Deutsch


Geostatistical simulation of mineral deposits for resource estimates and long-range planning is established. Professionals have access to the methodology, software and training to reliably calculate probabilistic resources. We have come a long way. In the early days, simulation amounted to multiple realizations with fixed input parameters within fixed geological boundaries...