Grasberg open pit to Grasberg block cave transition wetmuck and mine design

Ginting, Arjuna; Pascoe, Nicholas

doi:10.36487/acg_repo/2063_22

Cited by 4 publications

(4 citation statements)

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“…The wet muck was generally understood to originate from comminution within the draw column combined with high rainfall (Edgar et al 2020). The DOZ mine experienced its first spill in 2003 (Ginting & Pascoe 2020) and had recorded more than 1,900 spills as of 5 July 2019 (Figure 2). Spill frequency significantly increased from 2015 onwards due to the cave experiencing more saturation, which in turn led to an increasing drawpoint closure rate to maintain safety.…”

Section: History Of Wet Muck Spills At the Deep Ore Zone Minementioning

confidence: 99%

Development of a wet muck spill susceptibility tool for short-term prediction through a logistic regression approach

Varian¹,

McDougall²,

Ghadirianniari³

et al. 2022

Caving 2022: Fifth International Conference on Block and Sublevel Caving

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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.

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Section: History Of Wet Muck Spills At the Deep Ore Zone Minementioning

confidence: 99%

Development of a wet muck spill susceptibility tool for short-term prediction through a logistic regression approach

Varian¹,

McDougall²,

Ghadirianniari³

et al. 2022

Caving 2022: Fifth International Conference on Block and Sublevel Caving

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show abstract

“…The reasons for fragility of caves are varied, for example insufficient orebody knowledge and limited understanding of cave mechanics (geology and rock engineering are typically the reasons given for any shortcomings). The technical challenges of caving are well known if perhaps not necessarily well understood and are reasonably well documented (Flores-Gonzalez 2019; Ginting & Pascoe 2020;Edgar et al 2020;Simanjuntak et al 2020;Casten et al 2020).…”

Section: Figure 5 Concept Of Fragilitymentioning

confidence: 99%

Organising for the successful management of complex underground caving mines

Tshisens¹,

Moss²,

Sullivan³

et al. 2022

Caving 2022: Fifth International Conference on Block and Sublevel Caving

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The number of caving mines is increasing worldwide, with several new mines under development. While the technical challenges of caving are well known, they are not necessarily well understood. The execution of a development and operations plan is a complex process constrained by the realities of access, construction, ventilation, and mucking requirements, as well as uncertainties in ground conditions and rock mass response during caving. An equally important challenge exists around the organisation and management of resources to build and operate such mines. The challenges require a flexible and collaborative approach from the start that is based on sound engineering and performance measurement. The success of such an approach is illustrated through the progress of the PT Freeport Indonesia (PTFI) caves from the study stage to access development, infrastructure construction, cave establishment and ramping-up to the current production rate of 200,000 tons per day. Many technical lessons were learned along the way and various technologies were used to meet the challenges. More importantly was the creation of a coherent execution group with a clearly defined leadership team. Central to this was an underground steering committee comprising senior representatives from operations, engineering, geo-engineering, and safety. The committee's mandate was to determine solutions that addressed the strategic and tactical needs of the business rather than the short-term gains of the project. The collaborative leadership model used by PTFI was instrumental in the successful rampup of one of the largest caving complexes in the world.

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“…Mud entry in caving mining is generated by fine particles that mix with aqueous substances in different types of conditions, such as melting ice in the mountains, tailings filtration, aquifers, and weather conditions (snow and rain). This mixture travels through the column of broken material and reaches the drawpoints, causing water filtration and in some cases mud events, such as landslides, runoff, and mud rush (Ginting & Pascoe 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Wet muck entry has been recorded in different underground mines around the world, such as El Teniente in Chile (Ferrada 2011), Intermediate Ore Zone and Deep Ore Zone in Indonesia, Ekati in Canada, (Edgar et al 2020;Hubert et al 2000;Ginting & Pascoe 2020;Jakubec & Woodward 2020;Widijanto et al 2012). Some mitigation and control tools used range from drainage tunnels that allow the transfer of mud to lower levels or to the outside of the mine, remote-controlled equipment.…”

Section: Introductionmentioning

confidence: 99%

Modelling of wet muck entry at El Teniente for long-term planning

Salas¹,

Castro²,

Viera³

et al. 2022

Caving 2022: Fifth International Conference on Block and Sublevel Caving

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The intrusion of wet muck and fines and the potential of mud rushes pose safety risks for workers, equipment and infrastructure at El Teniente. Wet muck can also result in the loss of reserves because of the need to close drawpoints when large amounts of fine materials and moisture are observed. This paper presents the analysis and the development of a mathematical model to estimate wet muck entry for long-term planning applications at El Teniente. The models have been imbedded in BCRisk®, which is a machine-learning software that estimates hazards associated with the extraction process for underground mines. Four basins of El Teniente were included in the study of wet muck control: North, Center, South, and Reno. Each basin has mines with different characteristics in each exploitation sector. Consequently, models were built for each of the basins to represent its distinct reality.Several variables were investigated to define which determine the phenomenon. The variables include tonnage extracted or draw rate, amount of water entering the cave, season of the year, presence of mud in neighbouring drawpoints or sectors that have been closed due to wet muck above, and changes in surface or depressions. In addition, flow variables such as fragmentation and lithologies have been included and estimated with FlowSim 6.3® for increased precision. Results indicate that the classification models can reproduce the phenomenon with an acceptable precision of 71% and an average tonnage error per drawpoint of 7 to 10%. These results have been useful for long-term planning at El Teniente mine to predict wet muck entry and define when and where autonomous LHD may be required for the extraction of wet muck in the future.

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Grasberg open pit to Grasberg block cave transition wetmuck and mine design

Cited by 4 publications

References 0 publications

Development of a wet muck spill susceptibility tool for short-term prediction through a logistic regression approach

Development of a wet muck spill susceptibility tool for short-term prediction through a logistic regression approach

Organising for the successful management of complex underground caving mines

Modelling of wet muck entry at El Teniente for long-term planning

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