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Lalang, Marthen Pitherson Cahyadi

University of British Columbia

The Grasberg Block Cave (GBC) mine represents a transition from open-pit to underground mining to extract deeper resources. However, this transition requires the management of caving-induced surface subsidence and interactions between the cave and overlying open pit that could impact critical infrastructure located on surface in proximity to the open pit. Forecasting when and how these impacts will occur is currently carried out using advanced 3-D numerical modeling. However, this can be challenging, given the potential for uncertainty to cause predictions to not align with subsequent ground responses. To overcome this challenge, performance monitoring must be integrated with numerical models to track and validate forecasts and manage geological, parameter, and model uncertainties. This thesis develops a spatial and temporal framework to analyze subsidence caused by cave-pit interactions. Spatially, this uses LIDAR, which was highly effective at capturing the boundary of the fracture zone that develops during progressive cave breakthrough. Cross-correlation between monitoring data and numerical modeling helps to provide additional detection and insights into emerging slope deformation mechanisms developing in response to block caving. Temporally, adaptive learning provided an excellent tool for capturing the survivability of an area of interest before it collapses, and inverse velocity shows robust agreement in validating the results. In conclusion, this study highlights the importance of performance monitoring to bridge the gap between the value that numerical modeling forecasts can provide and the need to manage uncertainty and risk to protect critical mine infrastructure and assets. While numerical modeling is helpful for long-term strategic projections, the results presented in this thesis demonstrate that empirical trends based on monitoring data offer flexible supplementary prediction updates for short-term and intermittent periods.

Text

2024-09-11

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/89219

Geological Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/