relates to the practice of combining geology
Geology is the science comprising the study of solid Earth, the rocks of which it is composed, and the processes by which it evolves. Geology gives insight into the history of the Earth, as it provides the primary evidence for plate tectonics, the evolutionary history of life, and past climates...
Geostatistics is a branch of statistics focusing on spatial or spatiotemporal datasets. Developed originally to predict probability distributions of ore grades for mining operations, it is currently applied in diverse disciplines including petroleum geology, hydrogeology, hydrology, meteorology,...
Metallurgy is a domain of materials science that studies the physical and chemical behavior of metallic elements, their intermetallic compounds, and their mixtures, which are called alloys. It is also the technology of metals: the way in which science is applied to their practical use...
, or, more specifically, extractive metallurgy
Extractive metallurgy is the study of the processes used in the separation and concentration of raw materials. The field is an applied science, covering all aspects of the physical and chemical processes used to produce mineral-containing and metallic materials, sometimes for direct use as a...
, to create a spatially- or geologically-based predictive model for mineral processing
In the field of extractive metallurgy, mineral processing, also known as mineral dressing or ore dressing, is the process of separating commercially valuable minerals from their ores.-History:...
plants. It is used in the hard rock mining
Mining is the extraction of valuable minerals or other geological materials from the earth, from an ore body, vein or seam. The term also includes the removal of soil. Materials recovered by mining include base metals, precious metals, iron, uranium, coal, diamonds, limestone, oil shale, rock...
industry for risk management and mitigation during mineral processing plant design. It is also used, to a lesser extent, for production planning in highly variable ore deposits.
There are four important components or steps to developing a geometallurgical program,:
- the geologically-informed selection of a number of ore samples
- laboratory-scale test work to determine the ore's response to mineral processing unit operation
In chemical engineering and related fields, a unit operation is a basic step in a process.Unit operation involves bringing a physical change such as separation, crystallization, evaporation, filtration etc.. For example in milk processing, homogenization, pasteurization, chilling, and packaging are...
- the distribution of these parameters throughout the orebody using an accepted geostatistical technique
- the application of a mining sequence plan and mineral processing models to generate a prediction of the process plant behavior
The sample mass and size distribution requirements are dictated by the kind of mathematical model that will be used to simulate the process plant, and the test work required to provide the appropriate model parameters. Flotation testing usually requires several kg of sample and grinding/hardness testing can required between 2 and 300 kg.
The sample selection procedure is performed to optimize granularity
Granularity is the extent to which a system is broken down into small parts, either the system itself or its description or observation. It is the "extent to which a larger entity is subdivided...
, sample support, and cost. Samples are usually core sample
A core sample is a cylindrical section of a naturally occurring substance. Most core samples are obtained by drilling with special drills into the substance, for example sediment or rock, with a hollow steel tube called a core drill. The hole made for the core sample is called the "core hole". A...
s composited over the height of the mining bench. For hardness parameters, the variogram
In spatial statistics the theoretical variogram 2\gamma is a function describing the degree of spatial dependence of a spatial random field or stochastic process Z...
often increases rapidly near the origin and can reach the sill at distances significantly smaller than the typical drill hole collar spacing. For this reason the incremental model precision due to additional test work is often simply a consequence of the central limit theorem
In probability theory, the central limit theorem states conditions under which the mean of a sufficiently large number of independent random variables, each with finite mean and variance, will be approximately normally distributed. The central limit theorem has a number of variants. In its common...
, and secondary correlations are sought to increase the precision without incurring additional sampling and testing costs. These secondary correlations can involve multi-variable regression analysis
In statistics, regression analysis includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables...
with other, non-metallurgical, ore parameters and/or domaining by rock type, lithology, alteration, mineralogy
Mineralogy is the study of chemistry, crystal structure, and physical properties of minerals. Specific studies within mineralogy include the processes of mineral origin and formation, classification of minerals, their geographical distribution, as well as their utilization.-History:Early writing...
, or structural domains.
The following tests are commonly used for geometallurgical modeling:
- Bond ball mill work index test
- Modified or comparative Bond ball mill index
- Bond rod mill work index and Bond low energy impact crushing work index
- SMC test
- JK drop-weight test
- Point load index test
- Sag Power Index test (SPI(R))
- MFT test
- FKT, SKT, and SKT-WS tests
Kriging is a group of geostatistical techniques to interpolate the value of a random field at an unobserved location from observations of its value at nearby locations....
is the most common geostatistical method used for interpolating metallurgical index parameters and it is often applied on a domain basis. Classical geostatistics require that the estimation variable be additive, and there is currently some debate on the additive nature of the metallurgical index parameters measured by the above tests. The SPI(r) value is known not to be an additive parameter, however errors introduced by block kriging are not thought to be significant . These issues, among others, are being investigated as part of the Amira P843 research program on Geometallurgical mapping and mine modelling.
Mine plan and process models
The following process models are commonly applied to geometallurgy:
- The Bond equation
- The SPI calibration equation, CEET
- SMC model
- Aminpro-Grind, Aminpro-Flot models
- Isaaks, Edward H., and Srivastava, R. Mohan. An Introduction to Applied Geostatistics. Oxford University Press, Oxford, NY, USA, 1989.
- David, M., Handbook of Applied Advanced Geostatistical Ore Reserve Estimation. Elsevier, Amsterdam, 1988.
- Mineral Processing Plant Design, Practice, and Control - Proceedings. Ed. Mular, A., Halbe, D., and Barratt, D. Society for Mining, Metallurgy, and Exploration, Inc. 2002.
- Mineral Comminution Circuits - Their Operation and Optimisation. Ed. Napier-Munn, T.J., Morrell, S., Morrison, R.D., and Kojovic, T. JKMRC, The University of Queensland, 1996