Block Cave Mining Research Articles

Automated rock mass discontinuity set characterisation using amplitude and phase decomposition

Mapping structural discontinuities in subsurface environments is critical for several engineering applications. Most instances require stable rock mass to ensure safety while some require an unstable rock mass, such as in block-cave mining, for gravity induced smooth and continuous production of ore. Structural discontinuities have previously been mapped using manual, semi-automated and automated methods which have limitations in terms of required effort, processing time, definition of parameters and accuracy. Most of the semi-automated and automated approaches employ point cloud data, obtained either through structure from motion photogrammetry or laser scanner, and rely on point normal vectors in some form for discontinuity characterisation. Such methods can lead to inaccurate results in the presence of noise as normal vectors tend to show high variability in a local region. This study proposes a new automated algorithm that uses the spatial distribution of points on discontinuities to capture unique signatures in the form of a sinusoidal wave. Each discontinuity points are distinguished by unique amplitude and phase, achieved using fast Fourier transform (FFT), for characterisation in a 3-dimensional (3D) point cloud. The presented amplitude and phase decomposition (APD) approach requires minimal pre-processing and can be applied directly to a raw point cloud as filtering is inherently included in the signal processing. The method has been evaluated on an underground tunnel dataset, consisting of exposed structural discontinuity planes. The efficacy of the developed approach was tested against open-source semi-automated software (discontinuity set extractor), proprietary semi-automated software (Maptek PointStudio), manual segmentation using virtual compass plugin in open-source software (Cloud Compare), and other automated algorithmic approach based on point normal clustering and region growing. When compared against the manual discontinuity segmentation, the APD approach indicated the least error in estimating mean discontinuity dip angle and dip direction which was ±1.15° and ±1.39 with a dispersion error of ±2.24° and ±1.54°, respectively.

Operational mine planning in block cave mining: a simulation-optimisation approach

ABSTRACT Block cave mining operations face challenges to meet daily operational production targets. The optimistic long-term and medium-term plans along with uncertainty and the synergistic effect of the mechanical and structural failures in operational levels of the mine cause a significant deviation from production plan targets. The on-site tuning of the mining production targets in real time are neither the best practice nor the optimum approach to compensate for shortfalls in production. The objective of this paper is to develop a methodology that generates practical and near-optimal short-term mine plans for block caving operations in the presence of operational uncertainty. To accomplish this goal, we propose a simulation-optimisation approach using a Monte Carlo simulation model and a multi-objective non-linear goal programming model that takes into consideration operational constraints and uncertainties. In a case study, we compare the results of the proposed methodology against the mine plan and the historical production data of a copper block cave operation. The strengths and weaknesses of the model are presented and discussed.

Investigating the impact of the estimation error of fracture intensity (P32) on the evaluation of in-situ rock fragmentation and potential of blocks forming around tunnels

The purpose of this work is to highlight the impact of input parameters uncertainty in discrete fracture network (DFN) models and their engineering applications. We show how the error of an input parameter, here the volumetric discontinuity intensity P32, impacts the DFN model and two important rock mechanics engineering applications: the in-situ fragmentation size distribution and the potential of formation of removable blocks around tunnels, as two key parameters at block cave mining designs. The volumetric discontinuity intensity (P32) is estimated by two different approaches: the first one estimates P32 directly from 1D data and it is straightforward to implement, while the second one is based on the simulation of DFN models and needs both 1D and 2D data sets, which makes it less flexible and time consuming. The estimated values of P32 obtained from the direct approach are found to be more accurate than those by the simulation approach, with significant impacts observed in the constructed discrete fracture network models and in the estimation of the in-situ fragmentation size distribution and potential of formation of removable blocks around tunnels.

Semi-symmetrical production scheduling of an orebody for optimizing the depth of transitioning from open pit to block caving

A combination of open pit (OP) and underground (UG) mining methods may be applied for extraction of large scale orebodies. Although the optimization of production scheduling of each of these methods has been addressed separately, the simultaneous optimization of the whole mining operations has less been studied. However, such overall optimization strategy may enhance the net present value (NPV) of the adventure, determine the optimum transition depth (OTD), and help to manage natural resources accurately. This paper aims to determine an OTD between OP and block caving (BC) mining methods while scheduling an orebody entirely. In this regard, a semi-symmetrical integer programming (IP) model has been developed and implemented on a real orebody. The numerical results indicate that the OTD locates 10 m above the original OP bottom. By considering this level as the optimum separating limit of OP and UG mining operations, the NPV of the whole project will increase by up to 0.28%. Through the study, the definition of transition zone has been clarified and the transition capability has been introduced as a new term in mining literature.

A New Methodology Based on Hill of Value for Ore Reserve Selection in Long-Term Planning for Block Caving

The underground mining evolution for block cave mines in Chile and worldwide has made important strides in the last decades. Nonetheless, reserves determination in the initial stages of these types of projects—mainly for long-term planning—is not studied in as much detail as it should be, especially regarding the impact on the final value of the enterprise. Today, the first estimation of the size of a block cave mine, typically expressed in tons, tends to determine very large footprints and ore bodies. The resulting large-scale mine is obtained by applying the marginal cut-off grade (COG) to determine reserves. Yet, in many cases, it is possible to obtain an equal or higher benefit, extracting fewer reserves in less time, with a smaller active area, which significantly reduces the project’s uncertainty. To explore scenarios obtained by applying a higher marginal COG in the initial phases of the project, the Hill of Value methodology is used to estimate the net present value (NPV) in relation to the production rate and the COG. However, the application of this methodology considers certain simplifications that generate results which are not completely satisfactory in specific cases. This paper suggests an improvement of this method to obtain more reliable results regarding determination of a COG profile that will optimize the NPV of a block-cave project. The methodology was developed and applied in a massive polymetallic deposit with zinc, lead, and silver mineralization, corresponding to a real block caving project. The methodology provides NPV results that differ by approximately 15% in comparison to the real mine plan, while also being considerably simpler and faster to calculate. In summary, the proposed methodology provides a reasonable and fast procedure to estimate higher than marginal COG that increases the NPV of block cave mine projects.

Automated Core Logging Technology for Geotechnical Assessment: A Study on Core from the Cadia East Porphyry Deposit

Abstract The Cadia East porphyry deposit, located approximately 20 km south of Orange, New South Wales, Australia, contains a significant resource of copper and gold. This resource is hosted within the Forest Reefs Volcanics and is spatially and temporally associated with the Cadia Intrusive Complex. To extract ore, the underground mine currently uses the block cave mining method. The Cadia East geotechnical model provides data inputs into a range of numerical and empirical analysis methods that make up the foundation for mine design. These data provide input into the construction of stress models, caveability models, ground support design, and fragmentation analysis. This geotechnical model encompasses two commonly used rock classification systems that quantify ground conditions: (1) rock mass rating (RMR) and (2) rock tunneling quality index (Q index). The RMR and Q index are calculated from estimates of rock quality designation (RQD), number of fracture sets, fracture roughness, fracture alteration, and fracture spacing. Geologists and geotechnical engineers collect information used to produce these estimates by manually logging sections of drill core, a time-consuming task that can result in inconsistent data. Modern automated core scanning technologies offer opportunities to rapidly collect data from larger samples of drill core. These automated core logging systems generate large volumes of spatially and spectrally consistent data, including a model of the drill core surface from a laser profiling system. Core surface models are used to extract detailed measurements of fracture location, orientation, and roughness from oriented drill core. These data are combined with other morphological and mineralogical outputs from automated hyperspectral core logging systems to estimate RMR and the Q index systematically over contiguous drill core intervals. The goal of this study was to develop a proof-of-concept methodology that extracts geotechnical index parameters from hyperspectral and laser topographic data collected from oriented drill core. Hyperspectral data from the Cadia East mine were used in this case study to assess the methods. The results show that both morphological and mineralogical parameters that contribute to the RMR and Q index can be extracted from the automated core logging data. This approach provides an opportunity to capture consistent geologic, mineralogical, and geotechnical data at a scale that is too time-consuming to achieve via manual data collection.

Production Scheduling with Horizontal Mixing Simulation in Block Cave Mining

High production rates and low operating costs highlight block caving as one of the favorable underground mining methods. However, the uncertainties involved in the material flow make it complicated to optimize the production schedule for such operations. In this paper, a stochastic mixed-integer linear optimization model is proposed in order to capture horizontal mixing that occurs among the draw columns within the production scheduling optimization. The goal is to not only consider the material above each drawpoint for extraction from the same drawpoint, as traditional production scheduling does, but also to capture the horizontal movements among the adjacent draw columns. In this approach, different scenarios are generated to simulate the horizontal mixing among adjacent slices within a neighborhood radius. The best height of draw for draw columns is also calculated as part of the optimization. The model is tested for a block-cave mine with 640 drawpoints to feed a processing plant for 15 years. The resulting NPV is 473M$ while the deviations from the targets in all scenarios during the life of the mine are minimized. Using the proposed model will result in more reliable mine plans as it takes the horizontal mixing into account in addition to achieving the production goals. Using different penalties for grade deviations shows that the model is a flexible tool in which the mine planners can achieve their goals based on their priorities.

An Application of Rock Engineering System for Assessment of the Rock Mass Fragmentation: A Hybrid Approach and Case Study

Rock mass fragmentation process plays a major role in the design of the block cave mining. To assess rock mass fragmentation, identification and determination of influencing parameters are crucial. In most case studies, the cross-impact or indirect interaction of influencing parameters has not been considered in the assessment of rock mass fragmentation. The aim of this paper is to present a hybrid approach to consider the direct and indirect effects of influencing parameters on rock mass fragmentation by use of classic rock engineering system (RES) and matrices impact cross multiplication applied to classification method (MICMAC). The most important effective parameters in the system were identified and ranked based on both RES and hybrid approach. Thereafter, the indirect fragmentation index was calculated for RENO and Diablo Regimente mines in Chile and Kemess mine in Canada. An appropriate consistency was found between the results of the hybrid approach and available fragmentation data of the respective mines. The result of the analysis showed that the interaction of the geometrical and operational parameters has increased while the interaction of the geomechanical parameters, due to being less susceptible to change of the other parameters, has decreased in the hybrid approach compared to the RES. The geomechanical parameters showed the highest impact on the system and the lowest share of interaction in the system. The geometrical and operational parameters showed a high level of interaction, in the system, which the system had low influence on them.

Field validation of estimated primary fragment size distributions in a block cave mine

Field validation of estimated primary fragment size distributions in a block cave mine

Sequencing of ore columns for planning of large underground mines

Block caving is an underground mining technique which extracts ore from the base, rather than from the top, of typically massive deposits. Mining infrastructure is developed below the deposit before extraction commences. A network of tunnels provides access to a collection of drawpoints from which ore is hauled. With large deposits, not all drawpoints are developed simultaneously and the opening of drawpoints is sequenced to facilitate orderly extraction of ore columns above drawpoints. Sequencing fixes the initiation point for the entire block cave, or a part of it, as well as identifying the direction of cave advancement. The drawpoint opening sequence exerts influence on the block cave mine economics. This paper discusses the optimisation of sequencing based on the net present value associated with extraction over the life-of-mine. It is shown that the maximum attainable net present value is obtained by a sequence in which ore columns are ranked in descending order of value. If significant variation of grade is present inside columns, an iterative procedure is given which corrects the sequence which yields the maximum net present value. The sequence with maximum net present value may not be practical or attractive from a caving perspective. Systematic design of sequences which permit orderly development of a block cave is discussed. To provide context, the net present value obtained from these feasible sequences is compared with the maximum attainable net present value. It is shown that the best feasible sequences are preferentially initiated in zones with columns of high-grade ore.

Fuzzy-Based Prediction of Spatio-Temporal Distribution of Wet Muck in Block Cave Mine of PT Freeport Indonesia

Mud rushes, or wet muck spills, are hydro-geotechnical challenges in block cave mines where wet muck spills out of drawpoints formed by the accumulation of fine materials and water in drawbells. The purpose of this paper is to share the results of the developement of an improved predictive tool that can be used to manage wet muck spills. The tool was developed based on the hybrid modeling of wet muck distribution using fuzzy logic and fuzzy number operations. The fuzzy logic operations were applied to model the spatial distribution of wet muck classes, providing the spatial model of drawpoint status based on five contributing factors, i.e. the height of draw, the water content, the grain size of the fine material, rainfall, and no-mucking days. The fuzzy number operations were used in accordance with the mass balance principle to estimate the temporal distribution of wet muck that forms a mud deposit consisting of fine materials and water in a drawbell. The mass balance principle was expressed using the fuzzy ordinary differential equation, including the uncertainty of joining variables. A wet muck spill event at the Deep Ore Zone (DOZ) block cave mine of PT Freeport Indonesia was utilized as a case study as well as to validate the proposed method. The fuzzy-based approach shows promising results in predicting wet muck spill events.

APPLICATION OF MICROSEISMIC MONITORING IN UNDERGROUND BLOCK CAVING MINE

Induced mine activities could make impact to the rock’s stability. Block cave mine has some area where development of the progressing cave line and heading are disturbing and having risk to harm people working in the surrounding area. Rock mass in massive solid rock generates movement in order acting the stress that applied in the environment. Local movement in the mine where it’s caused by blasting – artificial source or passively occurs when the rock finds its stability is generating acoustic P and S waves. Microseismic monitoring system has been applied in the active mine area to ensure a safety production. This paper describes an application of real time microseismic monitoring system in underground mine operation to support a safety production.

Evaluation of bulk and particle sensor-based sorting systems for the New Afton block caving operation

Block and panel caving mines are increasingly being proposed for the excavation of massive ore-bodies located at depth. The lack of selectivity associated with the mining methods results in both ore and waste being caved and transported through material handling systems to the surface for processing and waste rock disposal. Sensor-based sorting systems provide an opportunity to automate the discrimination between ore grades and rock types, providing an enhanced level of selectivity for ore control and thereby improving mine productivity.To evaluate the potential to add value to a caving operation, a sensor-based ore sorting study, incorporating bulk and particle sorting systems, was carried out for the New Afton block cave mine. Results showed that rock from the copper-gold porphyry deposit is amenable to prompt gamma neutron activation analysis, and to X-ray fluorescence sensors. A conceptual flowsheet, where both technologies are used as separate unit operations, was evaluated. Test samples of varying copper head grades allowed an ore value calculation method to be developed based on the integration of continuous bulk sorting and particle sorting. The calculation method can be applied to block models of a future cave at New Afton and used to evaluate the change in the economic footprint. It was found that the concept demonstrated an improvement in the net smelter return of excavated material.

Stochastic optimisation of long-term block cave scheduling with hang-up and grade uncertainty

Mass mining methods provide alternatives in developing deeper and lower-grade mineral deposits. Consequently, block cave mining has been increasingly popular mass mining method, especially for large copper deposits currently being mined by open pit methods. This study adopts similar concepts as in stochastic open pit production planning to the planning of block cave mines, to evaluate their effectiveness in a different approach to mass mining. The main contribution of this study is the incorporation of the uncertainty of delays from hang-ups and grades directly into the production scheduling process of a cave mining operation. Hang-up uncertainty relates to the uncertainty linked to the occurrence of ore that clogs the production draw points. This clogging causes time delays in the production cycle leading to tonnage losses and additional costs. Grade uncertainty is incorporated by means of stochastic orebody simulations. Both uncertainty sources are directly linked to the extraction decisions and influence the optimized schedules. The proposed stochastic integer programming model is applied to the optimization of the long-term schedule of a large-scale, low-grade copper deposit by taking into account hang-up delays in block caving. The results of the optimization maximizing net present value clearly show the capability of the formulation to mitigate the effects of both grade and hang-up uncertainty.

Draw rate management system using mathematical programming in extraction sequence optimisation of block cave mining

Planning of caving operations poses complexities in different areas such as safety, ground control and production scheduling. Draw control is fundamental to the success of block-cave operation. Although some complex theories and mathematical draw control systems have been applied in block-cave mines, most of them did not have an exact production rate curve (PRC) to manage draw rates of drawpoints and are too complex to provide a solution for real block-caving mines. This paper presents a mixed-integer linear programming (MILP) model to optimise the extraction sequence of drawpoints over multiple time horizons of block-cave mines with respect to the draw control systems. Four draw rate strategies are formulated to guarantee practical solutions. Furthermore, dilution and caving are improved indirectly, because the method considers the draw rate strategy. Application and comparison of the four models for production scheduling based on draw control systems are presented using 298 drawpoints over 15 periods.

Draw rate management system using mathematical programming in extraction sequence optimisation of block cave mining

Planning of caving operations poses complexities in different areas such as safety, ground control and production scheduling. Draw control is fundamental to the success of block-cave operation. Although some complex theories and mathematical draw control systems have been applied in block-cave mines, most of them did not have an exact production rate curve (PRC) to manage draw rates of drawpoints and are too complex to provide a solution for real block-caving mines. This paper presents a mixed-integer linear programming (MILP) model to optimise the extraction sequence of drawpoints over multiple time horizons of block-cave mines with respect to the draw control systems. Four draw rate strategies are formulated to guarantee practical solutions. Furthermore, dilution and caving are improved indirectly, because the method considers the draw rate strategy. Application and comparison of the four models for production scheduling based on draw control systems are presented using 298 drawpoints over 15 periods.

Presentation of a multi-index clustering technique for the mathematical programming of block-cave scheduling

Long-term planning is one of the most important stages that determines the distribution of cash flows over the mine life and the feasibility of the project. However, it is not feasible in block caving to generate a production schedule that will provide optimal operating strategies without considering geotechnical constraints. This paper develops a mixed-integer linear programming (MILP) model to optimize the extraction sequence of drawpoints over multiple time horizons of block-cave mines with respect to the draw control systems. A multi-similarity index clustering technique to solve the MILP model in a reasonable time is also presented. Application and comparison of production scheduling based on the draw control system and clustering technique are illustrated using 325 drawpoints over 15 periods. The results show a significant reduction in the size of the MILP model, and in the time required to solve it.

Conditional draw control system in block-cave production scheduling using mathematical programming

Block caving is a complex and large-scale mining method. The application of block caving is for low-grade, caveable and massive ore-bodies. Among the underground mining methods available, caving methods are favoured because of their low cost and high level of production. Generating a production schedule that will provide optimal operating strategies without geotechnical constraints is not practical in block caving. Establishing relationships among draw columns to consider depletion rates of other draw columns is complex but essential to provide a reasonable solution for real block-caving mines. This paper presents a mixed-integer linear programming (MILP) model to optimise the extraction sequence of drawpoints over multiple time horizons of block-cave mines with respect to the draw control systems. Four resolutions are formulated in this paper to guarantee practical solutions with respect to draw control managing in mined areas according to the draw rate and conditional draw rate constraints. Application and comparison of the four resolutions for production scheduling based on the draw control systems are presented using 325 drawpoints over 15 periods. The performance was analysed based on maximising the net present value (NPV) at a discount rate of 12%. The maximum obtained NPV from of the proposed MILP models is $451.07M.

Preliminary investigation of rockmass response to undercut blasting in a block cave mining system using VRSV

Preliminary investigation of rockmass response to undercut blasting in a block cave mining system using VRSV

A discrete-event simulation tool for real-time management of pre-production development fleets in a block-caving project

The economic risk of the construction stage of a mining project results from the uncertainty in its duration and capital expenditure. Block-caving mining projects are characterised by long lead time to production, often longer than 15 years, and very high pre-production capital expenditure, resulting from large pre-production development requirements. As a result, the size and performance of mine development system are the parameters bearing most of the economic risk in the construction stage of block-caving projects. This study summarises the results of a research aiming to develop a management tool for real-time face allocation of equipment and operation performance modelling. The tool combines stochastic discrete-event simulation (DES) and Programme Evaluation Review Technique to optimise the size and performance of mine development system, thus minimising the duration of pre-production development, the highest risk parameter in block-cave projects. Furthermore, the model has an ample application potential in mining operations as a tool to assist management decisions in short-term planning and equipment dispatching system. The model was validated through its application in the Chuquicamata Underground Mining Project, in Chile.