Most new mining projects require an initial assessment of the locations and volumes of potential acid forming (PAF) waste that is likely to be moved and dumped in surface waste stockpiles. This requires sampling of the waste rock zones and submitting the samples for a series of tests. Key to the outcome of the waste characterisation process is obtaining sufficient samples that are representative of the various rock types both in number and spatial distribution.Various regulatory bodies throughout Australia and the rest of the world are currently struggling with how to define minimum amounts of sampling to achieve realistic estimates without imposing excessive costs and time constraints on a project.This paper addresses two aspects of the process: what constitutes a sufficient' number of samples how to use those samples in determining volumes of likely PAF material._x000D_
Geostatistical methods of characterising orebodies with large numbers of samples are routinely used in the mining industry by geologists and geostatisticians to estimate and classify Mineral Resources. In theory exactly the same methods can be used to estimate PAF waste locations and volumes.In practice the number and spatial distribution of dedicated PAF waste samples at feasibility stage is typically so small that it is almost impossible to estimate the spatial distribution of PAF material with any degree of confidence at all. Consequently, the common approach is to characterise a few samples from a lithological unit and then assume that they represent the unit as a whole. This approach, however, can be fraught with risk.This paper describes some of the findings of SRK's evaluation of several coal projects with respect to PAF waste evaluation and highlights some common misconceptions held by people working in this area that do not have a knowledge of statistics or geostatistics.CITATION:Kentwell, D, Garvie, A and Chapman, J, 2012. Adequacy of sampling and volume estimation for premining potential acid forming waste evaluation using statistical and geostatistical methods, in Proceedings Life-of-Mine 2012, pp 79-88 (The Australasian Institute of Mining and Metallurgy: Melbourne).