The deposits exploited in Australian open pit gold mines are often small and of low grade with highly variable gold distributions. Consequently, they require detailed grade control. The nature of these grade control programmes is outlined together with a description of the various computational methods used. Particular attention is given to geological input into the various stages of the grade control program so as to ensure the reliability of sampling; to aid the production of bench extraction outlines; and to predict and minimize dilution and ore loss. The application of geostatistical techniques in this respect is also critically examined.

Grade control and ore/waste delineation in open pit mining operations was traditionally based on the comparison of estimated grades with an economic cutoff. In the 1990s, an alternative approach to ore selection was applied and established, taking into account financial indicators through the so-called economic classification functions in combination with grade uncertainty assessment.

Geologists in some underground gold mines collect grab samples from broken ore piles or trucks as a method of grade control. It is often known as muck sampling. Generally, the goal of grab sampling is to try and reconcile the mined grade at the ore source to the predicted grade and/or predict the mill feed grade. The mass of the sample collected is limited by health and safety issues, as well as by the capacity of the laboratory to process the samples within a given time frame.

The objectives of mining grade control are presented and examples of the techniques used in various open pit and underground mines are used to define the attributes of good grade control. Reasons are discussed for the success of various improved practices.

Accurate recoverable resource estimation and grade control procedures are the foundation of successful mining ventures. Long, medium and short term planning in a mining operation are all dependent upon precise estimations. For example, poor estimation may result in the long term in a pit being incorrectly optimised, in the medium term cashflow forecasts may be disastrously inaccurate, and in the short term the allocation of ore and waste material by grade control may be erroneous.

This document describes an evaluation methodology and suite of guides that can be used to appraise the maturity of different geology-related activities within operations. These guides can be completed by on-site staff members in the form of a survey, or by a visiting professional observing an operation’s behaviours. The methodology is designed to evaluate each activity’s maturity using different methods. There are three key methods: a) the Maturity Index, b) the Task Description and c) Improvement Areas. These methods examine the activity from different angles and should align if the results are consistent. The final results can be combined to produce an overall appraisal of the geoscientific information management environment. <...>

The Shewhart X— and R charts are still the most popular control charts in use today for continuous monitoring of quality data. However, for these charts to function properly, the underlying assumption of normality and independence of data must be satisfied. When either independence and/or normality of data are not present, which is a common feature of ore quality data, an application of the conventional Shewhart X— and R charts may introduce false alarms in the analysis of the data.

Mining reconciliation is the comparison of estimated tonnage, grade and metal with actual measurements. The aims are to measure the performance of the operation, support the calculation of the mineral asset, validate the Mineral Resource and Ore Reserve estimates, and provide key performance indicators for short and long-term control (Morley, 2003). Ongoing, regular and efficient reconciliation should also highlight improvement opportunities and allow for proactive short-term forecasting by providing reliable calibrations to critical estimates. The concept is that of “measure, control and improve”.  <...>

The optimisation of a mining operation requires precise ore grade control, metallurgical accounting, and laboratory sampling protocols, which are implemented by using accurate and flawless sampling systems. Good sampling practices, and sampling technologies in these fields have been historically poor and too many existing sampling systems available on the market are flawed in many ways.

Metal mining operations, in particular gold mining operations, use intensive ore control procedures in order to manage the extraction of ore zones from benches containing both ore and waste material. Typical grade control procedures rely on blast hole samples to indicate ore grade. Statistical techniques and geological controls are then used to create two-dimensional polygons, which indicate zones of material designated as ore. These ore-polygons are calculated using preblast material locations and are generally not corrected for rock movement caused by blasting.