A Multi-Criteria Ranking Approach for Assessment of Geotechnical Data Uncertainty

DOI

10.2991/978-94-6463-900-1_18How to use a DOI?

Keywords

data uncertainty; data confidence; quantitative reliability assessment; coefficient of variation; factor of safety; probability of failure

Abstract

Timely prediction of a slope failure aimed at minimizing its negative impact on the personnel safety, in-pit infrastructure and business profitability is the key risk management requirement at a modern-day open pit operation. The primary tool for the slope failure prediction is the numerical modelling, the results of which are highly dependent on the reliability of input data. There are various guidelines on the data confidence assessment, typically in qualitative/ descriptive terms (e.g. Steffen 1997, Haile 2004, Read & Stacey 2009, Sullivan 2013); however, a tool for a comprehensive quantitative assessment of geotechnical data uncertainty is still to emerge. In an effort to account for the data uncertainty in quantitative terms, a multi-criteria ranking approach is presented in this paper. The method comprises ranking the quantity and quality of the geotechnical information obtained from various sources, including core logs, historical maps, hand- and digital mapping, geophysical surveys, laboratory and field-testing. The method has been tested by the authors at a number of open pit projects at various stages of lifecycle and proved reasonably reliable, relatively easy to use and objective.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - V. Louchnikov
AU  - D. Selivanov
AU  - V. Berezhnoi
PY  - 2025
DA  - 2025/12/07
TI  - A Multi-Criteria Ranking Approach for Assessment of Geotechnical Data Uncertainty
BT  - Proceedings of the Rocscience International Conference 2025 (RIC 2025)
PB  - Atlantis Press
SP  - 188
EP  - 202
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-900-1_18
DO  - 10.2991/978-94-6463-900-1_18
ID  - Louchnikov2025
ER  -