Key challenges integrating caving geomechanics simulation into mine planning processes start with the considerable effort to build realistic models and to map production schedules and cave back geometries into the simulation. Currently, calibrating parameters for the complex failure mechanisms that define the interface (cave back, possible airgap, muck pile) between solid and flow domain can be extremely time consuming. This also often requires a high level of expertise in modelling. This work investigates the numerical efficiency of automated mesh and model building strategies and advantages of using high-performance computing on regular fine grids for non-linear finite element simulation. This allows direct mapping of cellular automaton results, and in return, predictions of rock mass failure without loss of accuracy at a higher frequency, maximising the use of information available from calibrated flow models for production scheduling. An important goal for such models must be the ability to simulate cave growth in complex geological settings and replicate realistic behaviour for relevant benchmark problems that reflect industry experience in block caving. These automated processes will not just accelerate the cave modelling processes and reduce manual processing time but also allow use of the full simulation cycle in case studies, sensitivity analysis and optimisation in an environment of uncertainty and constant changes to the available data. Integrated simulation and optimisation tools significantly improve understanding of realistic geomechanics behaviour driven by the inherent characteristics of the rock mass and structural geological setting, by the extraction strategy and by other engineering decisions (interaction with underground infrastructure). This greater level of understanding reflects in key performance indicators related to safety, revenue maximisation (strategy on how best to exploit the mineral resource), and operation excellence (productivity).

Carrapateena is a copper-gold deposit hosted in a brecciated granite complex, located 460 km north of Adelaide, South Australia. The deposit will be mined by the sublevel cave mining method. The ore is located below 500 m of unmineralised rock cover with six horizontal domains of various rock strengths, and therefore, fragmentation characteristics. Preliminary testwork of two predominant cover domains has shown that they are likely to break up substantially compared to the ore being mined. Furthermore, the cover sequence hosts two groundwater units of varying permeability which will be intersected by the cave zone. This paper discusses the work in preparation for the mining of the deposit in late 2019, with a focus on: Understanding the orebody and cover sequence material. Methodologies to understand and manage water ingress into the cave zone. Methodology used for modelling of fines ingress. Discussion of cave marker placement, and techniques and their purpose. Methodologies to obtain the data required to inform safe draw control decisions during ramp-up and mining of the operation.

Depleting global copper resources and declining discovery rates are driving a step-change in the copper mining industry as open pit mines transition underground and exploration for new deposits moves deeper. The need to exploit deeper, larger and lower grade copper deposits has resulted in the emergence of a technically challenging underground mass mining method called block caving. To improve shareholder returns, mining companies rising expectations for block cave mines are currently pushing the limits of existing knowledge and positioning larger and deeper projects in uncharted territory from a geotechnical risk and cost perspective. This paper addresses unconsidered geotechnical risks in discounted cash flow (DCF) analysis by introducing Monte Carlo simulation and decision tree analysis into a DCF model for the feasibility stage Carrapateena block cave expansion, currently being advanced by OZ Minerals.As a brownfield block cave development project expected to transition from sublevel caving to block caving, the ability to pivot the production strategy in response to downside risks encountered during block cave development and ramp-up was the focus of this paper. Dynamic modelling of geotechnical uncertainty was conducted to provide insight into how uncertainty can be resolved through time, as management decisions are made in response to uncertain events during the development and ramp-up of a block cave project. A dynamic DCF model was created to help assess the risks around the schedule, including the ramp-up and the undercutting phase of the project, while also using a decision tree to determine the best decision for the project overall.The results from the simulation demonstrated an average recovery of approximately AUD 20 million to the valuation for Carrapateena and increased the minimum incremental net present value to be greater than zero, confirming based on the model assumptions and probability distributions that OZ Minerals should decide to pursue the expansion. An additional simulation, focusing on the value of the decision tree itself, indicated that management decisions could minimise the downside risks of delays by up to 15% on the base NPV, supporting the use of decision trees in DCF analysis.

Carrapateena is an underground sublevel cave operation. To maximise future value from the Carrapateena copper-gold resource, an expansion study has been completed to feasibility study level to assess a larger block cave expansion below the current sublevel cave. This paper will summarise Carrapateena block cave mine design and planning from pre-feasibility to feasibility study.Emphasis will be on the footprint determination, mine layout, and production ramp-up. It will also discuss the material handling system selection, ventilation design and mine dewatering. As the block cave will be built below the sublevel cave operation, the transit from the sublevel cave to a block cave mine will be discussed, particularly on production plan, risk control and resources management.

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