Monitoring of fracture limits, cave backs and drawpoint fragmentation at both the Grasberg Block Cave (GBC) and Deep Mill Level Zone (DMLZ) caves at PT Freeport Indonesia's operations suggest that Cave Propagation Factor (CPF), weak and persistent vein intensity and hydrofracture spacing exert a strong control on the caving rate and primary fragmentation within the cave back. CPF in this case is defined as the ratio of cave back stress to defected rock strength and can vary significantly across the cave back, both due to variability in vein mineralogy and intensity and complex cave back geometries. Cave back stress is understood through 3D elastic modelling of anticipated cave shapes (fracture limits) while point load indices, weak and persistent vein intensity and Synthetic Rock Mass (SRM) testing are used to understand the variability in strength and fragmentation potential of the sparsely jointed, massive to heavily veined rock mass domains. When coupled with predictive relations for secondary fragmentation, these ultimately led to the development of a methodology for forecasting of caving rate and primary fragmentation in the cave back, the fragmentation (including oversize and fines) reporting to the drawpoints and the associated hangup frequency and productivity. These forecasts are presented in the form of block models, forecast maps and drawpoint-based charts. When calibrated against monitored cave back and drawpoint performance these can be used to assist in more local cave back shaping and preconditioning (function of caving rate), recovery estimation and secondary breakage planning (function of productivity) and management of wet muck and mill throughput (function of fines entry).

PT Freeport Indonesia's (PTFI) Grasberg mining complex consists of some of the largest and deepest mines in the world, set within a complex geological, hydrogeological, and geotechnical setting. A risk-based approach to scope definition is implemented practically to manage hazards at underground operations. The approach focuses on identifying hazards, managing those hazards, and communicating risk from planning through operational stages. Risk management is centred around an online platform that enables users to reference hazards and determine initial, current, and residual risk ratings. PTFI's approach to risk assessment enables management to understand the divisional risk across multiple technical disciplines and focus their efforts on scope definition, manpower and budget allocation to promote safety and achieve stated production targets. This paper provides details of PTFI's approach to risk management, highlights challenges and realised benefits, and outlines the path forward for continued risk-based scope definition and hazard management.

Fragmentation production and associated hang-up frequency and fines entry forecasts have been incorporated into the existing PCBC-based production forecasting workflow at PT Freeport Indonesia. These forecasts inform numerous operational aspects including draw scheduling, production planning, cave shape targeting and wet muck hazard management. This paper first describes two key aspects of the workflow that have enabled forecasting of these quantities at the drawpoint-month level for the life-of-mine: 1) block models of expected primary and secondary fragmentation, derived from block models of point load index, cave back stress potential and volumetric vein/fracture intensity measures of vein point load index and 2) an empirical relation between hang-up frequency, draw rate and rock block size and strength, derived from reconciliation of forecast versus measured hang-up frequency at GBC and DMLZ. This is followed by an overview of the forecast outputs and the reconciliation process, which is central to calibration of the methodology and the production of a reliable forecast. This process relies on rapid, accessible and up-to-date visualisation of the forecast and actual data in the form of time-based heat maps and charts, which are also used to communicate the forecast outputs to all stakeholders.

A geotechnical model is the fundamental basis for the design of an open pit and underground mine. A fully understood and representative geotechnical model will provide information on the engineering characteristics of the rock mass, defining how it is going to behave during mining. The model is composed of individual domains, each comprised of materials exhibiting internally similar geotechnical properties. Defining these domains and fully understanding what is critical to the excavation and the associated risks will enable the mine planners to design the optimal mine. A geotechnical model that will add value to a mine design should be developed based on a thorough understanding of the 3D geology, structure and, where relevant, alteration and weathering states of the deposit and how these impact the engineering properties. The geotechnical specialist should have a good understanding of the risks and limitations of each individual model and how these will impact on developing the geotechnical domains. A representative geotechnical model is only as good as the data that is available for the deposit. This paper presents the different types of data used to develop the geotechnical model for the Cukaru Peki deposit and the approach adopted for creating a representative geotechnical model that was used for mine planning.A geotechnical model that will add value to a mine design should be developed based on a thorough understanding of the geology, structure and, where relevant, alteration and weathering states of the deposit https://papers.acg.uwa.edu.au/p/1815_62_Llewelyn/ Geotechnical data collection and approach to modelling for the Cukaru Peki deposit K Llewelyn et al. 784Caving 2018, Vancouver, Canada and how these impact the engineering properties. The geotechnical specialist should have a good understanding of the risks and limitations of each individual model and how these will impact on developing the geotechnical domains.This paper presents the different types of data used to develop the geotechnical model for the Cukaru Peki deposit and the approach adopted for creating a representative geotechnical model that was used for mine planning.

The Grasberg mining complex in Papua, Indonesia, consists of three caving operations and an open stope mine. Two of the caves, the Grasberg Block Cave (GBC) and the Deep Mill Level Zone (DMLZ), are ramping up to full production, while the Deep Ore Zone (DOZ) cave will cease operations in 2022. The DOZ has had a history of production interruptions due to wet muck spill events. The newer caves expect to be affected by similar wet muck hazards due to the presence of fines and saturated material at the muck pile, overlying open pit in the case of the GBC and overlying caves in the case of the DMLZ, high annual rainfall, and complex topography at the subsidence that directs surface and groundwater into the cave.To proactively manage this hazard, experience from the DOZ cave mine is being applied to improve the understanding of drawpoint wet muck spill susceptibility. The combination of fines generated through secondary fragmentation from the high draw columns and saturation from the intense surface and groundwater inflow results in wet muck material at the drawpoint, providing the cause while mucking activities provide the trigger. Other contributing factors included in the analysis are the uniformity of draw and neighbouring drawpoint conditions.Although the consequences of wet muck spill events are high, they are still relatively rare, resulting in an imbalanced dataset. To overcome this challenge, cost-sensitive learning is incorporated into the logistic regression model for significant variables selection, thus developing a wet muck susceptibility tool. This tool aims to identify individual drawpoint susceptibility to wet muck spill events based on a simple material classification and measures of draw performance. The approach has been successful in describing historical drawpoint susceptibility at the DOZ. Furthermore, this study provides a concept applicable to other wet muck susceptible cave mines.