Estimation of fines and solids content in tailings oil sands deposits is imperative for tailings planning as well as reporting tailings inventory to the regulator. This report reviews the development of a proper procedure for the engineering assessment of uncertainty in reported tailings mass/ volume as a function of data spacing.
The major cost associated with open pit mine operations is waste stripping. While the steepening of slope angles reduces the stripping ratio, and hence operational costs, it also increases the likelihood of failure. Major slope failures incur significant cost elements including clean-up, disruption to mine operation, and damage to mining equipment and in some cases loss of reserves. Geotechnical engineers are often faced with the difficult task of finding the balance between slope optimisation and acceptable risk related to the likelihood of large slope failures. Technological advancements have allowed for the development of larger and deeper open pit operations, but have also created higher economic impact from potential slope failures. Given that the aim of mining operators is to maximise overall profits, it is surprising that most slope designs are based on deterministic design approaches, and limited attention is given to quantifying uncertainties in the geotechnical model. As most major decisions in the mining industry are made by senior management staff and financial staff, any attempt on linking slope stability analysis results with monetary values would improve the critical communication between geotechnical designers and decision-makers. Using Cowal Gold Mine as a case study, this paper illustrates economic risk caused by geotechnical uncertainties. The geotechnical risk estimate is generally subjective due to geotechnical engineers having to rely on limited data and engineering judgement. Geotechnical risk is compared against economic factors that are often perceived as important variables in mining operations.
Mining in residual soils is a characteristic of some open pit mines, particularly those mines in the tropical and sub-tropical regions. With residual soils prevalence on the earths surface almost as common as that of sedimentary rocks (Wesley 2013), mining in such soils requires special understanding of the behaviour and characteristics of the residual soil to determine slope designs that are both safe and economic. Due to the presence of relict structures, and the relatively low strength of the residual soils and weathered rock, design slope angles in these materials should be developed by blending the results of the kinematic assessments of geologic structures with rock mass stability analyses and traditional soil mechanics (Newcomen & Burton 2000). It is thus imperative that geotechnical designs should be site/location-specific and based on soils field performance, back-analyses and risk zoning. Understanding the variability of these materials is important for developing robust designs. This paper outlines the different aspects that are to be considered when conducting slope designs in residual soils, and in particular, saprolites, and summarises shear strength data from various mine sites that highlights the uncertainty associated with these parameters.
Uncertainty in mining geomechanics and geotechnical engineering is a broad term that accounts for natural variability, lack of data, and lack of knowledge. Reducing uncertainty is a key component of the mining study process and in managing geomechanical/geotechnical risk. Understanding and reducing uncertainty is also a key activity in the design process to ensure that designs are robust and resilient. A variety of methods are used in geomechanical design including empirical, analytical and numerical modelling. All design methods require inputs, and these are based on data from core logging, mapping, laboratory testing, field observations, and monitoring. This data then must be compiled and interpreted so that meaningful and reliable design inputs with a reliability that is commensurate with the level of design (scoping through to operational) can be derived. This includes the development of the geomechanical or geotechnical model. The uncertainty of the geotechnical model is often described in terms of confidence or reliability. Currently, very little quantitative guidance exists in the literature on assessing the confidence level of geotechnical studies and design, although there have been attempts by various authors (Haile 2004; Haines et al. 2006; Read 2009; Dunn et al. 2011) to qualitatively describe what level of geotechnical data is required. Several authors have outlined methods that could be applied to assess the reliability of geotechnical data (Read 2013; Fillion & Hadjigeorgiou 2013; Dunn 2015). Data from a range of projects are reviewed and summarised and an attempt made to quantify the uncertainty for some data, and illustrate the impact this can have on designs and commonly used design acceptance criteria.