Conference Proceedings
AusRock 2014: Third Australasian Ground Control in Mining Conference
Conference Proceedings
AusRock 2014: Third Australasian Ground Control in Mining Conference
Geotechnical Models and Data Confidence in Mining Geotechnical Design
The geotechnical model is the cornerstone of any mining geotechnical design and as such the confidence level and reliability of the geotechnical model is paramount. The geotechnical model confidence level needs to be commensurate with the level of design that is being applied or study that is being undertaken. The geotechnical model is made up of several components and the reliability of the data underlying these components ultimately determines the reliability of the geotechnical model.Data reliability is linked to the quantity of data collected, the spatial distribution of the data collected, quality of the data collection and the interpretation of the data. In a typical project, there is an opportunity to improve data reliability through the scoping, prefeasibility, feasibility and final design and implementation stages.Currently, very little quantitative guidance exists in the literature on assessing the confidence level of geotechnical studies, although there have been attempts by various authors (Haile, 2004; Haines, Swart and Kruger, 2006; Read and Stacey, 2009; Dunn, Basson and Parrott, 2011) to qualitatively describe what level of geotechnical data is required. Recently a number of authors (Read, 2013; Fillion and Hadjigeorgiou, 2013; Thomas, 2013) have outlined methods that could be applied to assess the reliability of some types of geotechnical data that are used in the development of geotechnical models.This paper briefly discusses some of the factors influencing data reliability and the geotechnical model confidence and some of the tools available.CITATION:Dunn, M J, 2014. Geotechnical models and data confidence in mining geotechnical design, in Proceedings AusRock 2014: Third Australasian Ground Control in Mining Conference , pp 127-134 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Contributor(s):
M J Dunn
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- Published: 2014
- PDF Size: 0.28 Mb.
- Unique ID: P201412015