Natural Resources Engineering - Master's Theses

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Adapting methodologies from the forestry industry to measure the productivity of underground hard rock mining equipment
(2017-08-30) Hauta, Rebecca Lynn
The purpose of this dissertation is to develop and apply a framework to characterize the ground support installation component of the mining development cycle in underground hard rock mines for the purposes of comparing equipment. A secondary goal is to identify opportunities to improve the productivity of the ground support installation process. It was found that the forestry industry faces similar challenges as the mining industry when measuring equipment output in a variable environment where equipment productivity is affected by a range of external conditions. Despite this challenge, forestry researchers successfully developed and applied a standardized methodology and nomenclature to measure the productivity of equipment for the purposes of equipment and process comparison in variable external conditions. The methodology used in the forestry industry was modified to measure mechanized and semimechanized ground support installation productivity in three Canadian underground hard rock mines. Furthermore, opportunities to improve the ground support installation process were identified. This framework can be modified to measure and compare other types of mining equipment. By using a standardized methodology to measure, compare and improve mining processes, development and production rates can be increased in underground hard rock mines. In summary, a framework was adapted from the forestry industry to measure and compare the productivity of the ground support installation cycle in three Canadian hard rock mines, and opportunities to improve the process were found.
Application of GenRel for maintainability analysis of underground mining equipment: based on case studies of two hoist systems
(Laurentian University of Sudbury, 2015-01-29) Xu, Chao
With the increasing costs of extracting ores, mines are becoming more mechanized and automated. Mechanization and automation can make considerable contributions to mine productivity, but equipment failures and maintenance have an impact on the profit. Implementing maintenance at suitable time intervals can save money and improve the reliability and maintainability of mining equipment. This thesis focuses on maintainability prediction of mining machinery. For this purpose, a software tool, GenRel, was developed at the Laurentian University Mining Automation Laboratory (LUMAL). GenRel is based on the application of genetic algorithms (GAs) to simulate the failure/repair occurrences during the operational life of equipment. In GenRel it is assumed that failures of mining equipment caused by an array of factors follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest using genetic algorithms (GAs) coupled with a number of statistical techniques. This thesis will show the applicability and limitation of GenRel through case studies, especially in using discrete probability distribution function. One of the objectives of this thesis is to improve GenRel. A discrete probability distribution function named Poisson is added in the pool of available probabilities functions. After improving and enhancing GenRel, the author carries out two groups of case studies. The objectives of the case studies include an assessment of the applicability of GenRel using real-life data and an investigation of the relationship between data size and prediction results. Discrete and continuous distribution functions will be applied on the same input data. The data used in case studies is compiled from failure records of two hoist systems at different iv mine sites from the Sudbury area in Ontario, Canada. The first group of case studies involves maintainability analysis and predictions for a 3-month operating period and a six-month operating period of a hoist system. The second group of case studies investigates the applicability of GenRel as a maintainability analysis tool using historical failure/repair data from another mine hoist system in three different time periods, three months, six months and one year. Both groups apply two different distribution probability functions (discrete and continuous) to investigate the best fit of the applied data sets, and then make a comparative analysis. In each case study, a statistical test is carried out to examine the similarity between the predicted data set with the real-life data set in the same time period. In all case studies, no significant impact of the data size on the applicability of GenRel was observed. In continuous distribution fitting, GenRel demonstrated its capability of predicting future data with data size ranging from 166 to 762. In discrete probability fitting, the case studies indicated to a degree the applicability of GenRel for the hoist systems at Mine A and Mine B. In the discussion and conclusion sections, the author discloses the findings from the case studies and suggests future research direction.
Application of seismic monitoring in caving mines
(Laurentian University of Sudbury, 2013-10-10) Abolfazlzadeh, Yousef
Comprehensive and reliable seismic analysis techniques can aid in achieving successful inference of rockmass behaviour in different stages of the caving process. This case study is based on field data from Telfer sublevel caving mine in Western Australia. A seismic monitoring database was collected during cave progression and breaking into an open pit 550 m above the first caving lift. Five seismic analyses were used for interpreting the seismic events. Interpretation of the seismic data identifies the main effects of the geological features on the rockmass behaviour and the cave evolution. Three spatial zones and four important time periods are defined through seismic data analysis. This thesis also investigates correlations between the seismic event rate, the rate of the seismogenic zone migration, mucking rate, Apparent Stress History, Cumulative Apparent Volume rate and cave behaviour, in order to determine failure mechanisms that control cave evolution at Telfer Gold mine.
Broadband optical wireless communications for the teleoperation of mining equipment
(2017-06-01) Frutuoso Barroso, Alberto Rui
The current level of technological advancement of our civilization serving more than seven billion human population requires new sources of biotic and abiotic natural resources. The depletion and scarcity of high-grade mineral deposits in dry land are forcing the Natural Re- sources industry to look for alternate sources in underwater environments and outer space, requiring the creation of reliable broadband omnidirectional wireless communication systems that allows the teleoperation of exploration and production equipment. Within these ob- jectives, Optical Wireless Communications (OWC) are starting to be used as an alternative or complement to standard radio systems, due to important advantages that optical wave- lengths have to transmit data: potential for Terabit/s bit rates, broadband operation in underwater environments, energy e ciency and better protection against interference and eavesdropping. This research focus in two crucial design aspects required to implement broadband OWC systems for the teleoperation of mining equipment: high bandwidth wide beam photon emission and low noise omnidirectional Free-Space Optical (FSO) receivers. Novel OWC omnidirectional receivers using guided wavelength-shifting photon concentra- tion are experimented in over 100 meters range vehicle teleoperation.
Commissioning and verification of compressed air yield on the hydraulic air compressor demonstrator
(2018-03-28) Sivret, Justin
The completion of the hydraulic air compressor (HAC) demonstrator at Dynamic Earth in Sudbury, Ontario marks the beginning of a series of research activities to increase the efficiency of compressed air production and build confidence in future commercial applications. Before any proper experiments could be conducted on the HAC Demonstrator a series of commissioning activities and testing was completed to i) calibrate the instruments, ii) check and understand losses, and iii) verify, or otherwise, some of the assumptions made during the system design. The practical work associated with this master’s thesis included the development of a human machine interface (HMI) to allow for automated control of the HAC. Instrumentation and control equipment was installed and routed to a control panel providing conditioned power and routes for signals. Within the control panel, these are digitised and transmitted using TCP/ IP/ MODBUS protocol, operating over a TopServer (Software toolbox, 2009) OPC backbone. The OPC Client toolbox in MATLAB was adopted to interface with the OPC Server, and MATLAB’s App Designer adopted for authoring the HMI. All I/O functionality is thus routed to MATLAB in which a PID control loop was established between the HAC separator water level and the HAC’s compressed air motorized globe valve. Thus, a reliable, flexible, scientific control interface and data storage infrastructure was established for this novel compression plant as part of the master’s work. The HAC Demonstrator can now effectively run a variety of experiments while recording a wide range of data for analysis. To date, a series of 90 benchmark tests for compressor performance have been completed in a systematic manner on the demonstrator to create a database of real HAC operating conditions. This thesis thus represents the first formal publication of the HAC Demonstrator’s complete performance under the baseline operating conditions. Previous predictions of the compressed air yield and efficiency of a HAC of this size have been made by Millar (2014), upgraded to weakly couple solubility loss by Pavese et al. (2016) and refined using Young’s (2017) detailed coupling of solubility and psychrometric phenomena. The predictions made by these models have been tested. The 1D hydrodynamic solubility models also predicted a small beneficial ‘airlift’ effect on compressor performance, due to exsolution of formerly dissolved compressed gas, that has also been reported upon. One unexpectedly important factor that has been found to affect HAC performance that was not anticipated in any of the models included the absolute surface roughness of rubber lined pipe, in comparison to that of bare steel pipe. High precision experiments are reported upon that have produced reliable values for absolute surface roughness for rubber lining materials, that have now been adopted in the HAC models, and may be adopted more widely too. The occurrence of detrainment, water jet-free fall and air re-entrainment is speculated upon as the source of previously unreported loss in the air-water mixing process, based on pressure profiling observations undertaken over the complete performance envelope of the Dynamic Earth HAC Demonstrator.
Computer-based application to assess gross motor skills using Microsoft Kinect sensor
(2018-03-07) Bragança Moraes, Arina
The performance of a fundamental motor skill in early childhood can be investigated using diverse assessment tools. Although the classical tests are reliable and useful for motor skills assessment, they have some limitations. The launch of the Microsoft Kinect marked a revolutionary advancement for developers thanks to the depth camera and its affordable price. This work aims to develop a reliable computer-based application using the Microsoft Kinect sensor to implement the third version of the Test of Gross Motor Development (TGMD-3). The assessment consists of customized algorithms that verify if the 3D position of the most relevant joints for each subtest varies along time according to the respective performance criteria. The proposed system returns an immediate feedback to the participant, indicating if s/he passes or fails the selected subtest. The results revealed the computer-based application for assessing gross motor skills is accurate, although it is limited by the space requirements.
Cross-linked polymers of phenylacetylene and 1,3-diethynylbenzene: new polymer precursors for nanoporous carbon materials for supercapacitors and gas storage
(Laurentian University of Sudbury, 2015-01-09) Grundy, Mark
The increasing threats of global warming, rapid depletion of fossil fuels, and increasing energy demands are driving an enormous amount of research into clean renewable sources of energy, flue gas capture technologies, and environmentally friendly energy storage devices, to name a few. Activated carbons present a multipurpose material commonly used in many of these increasingly popular green technologies. A wide range of cross-linked acetylenic polymers of phenylacetylene and 1,3- diethynylbenzene were synthesized and investigated in this thesis to generate materials for electrochemical double layer capacitors, CO2 capture, and hydrogen storage. Chemical activation of the copolymers in the presence of KOH was shown to produce highly microporous carbons with various textural properties. The specific cross-linking densities of the polymer precursors prior to carbonization were shown to greatly affect the carbon yield, surface area, pore volumes and pore sizes of the carbons produced. Electrochemical measurements of the activated carbons showed their impressive performances as capacitor materials, with high specific capacitances (up to 446 F g−1 at 0.5 A g−1 in 3-electrode cell) and long cycle life. Gas sorption studies also demonstrated impressive H2 and CO2 adsorption capacities (up to 2.66 wt% or 13.3 mmol g−1 for H2 adsorption at 77 K and 1 atm, and up to 30.6 wt% or 6.95 mmol g−1 for CO2 adsorption at 273 K and 1 atm). Owing to the high content of pendent alkyne groups in these polymers, complexation reactions with metallic carbonyl ligands are able to provide an effective iv way of dispersing metallic and metal oxide nanoparticles within the synthesized copolymers, which could provide additional pseudocapacitive properties. An appropriate copolymer with high alkyne content was subjected to complexation with Co2(CO)8, and subsequently carbonized and oxidized to yield carbon-supported CoxOy/Co nanoparticles (CoxOy@C-CPD76%). In addition to pseudocapacitive contributions, the cobalt species also effectively catalyzed the production of graphitic networks within the carbon support, improving their conductive properties. Electrochemical measurements demonstrated impressive specific capacitance (310 F g−1 at 0.1 A g−1) compared with non-activated carbons (160 – 177 F g−1 at 0.1 A g−1) synthesized at identical conditions, and provided a large stable potential window (1.4 V) in an aqueous KOH solution. The combined electrochemical double layer capacitance and pseudocapactiance behaviour of the carbon and CoxOy/Co also provided improved energy densities (21 W h kg−1), and uncompromised power densities (2017 W kg−1) compared with the pristine carbons (~2034 W kg−1).
Design, construction and testing of a Tesla Turbine
(2016-02-26) Holland, Kris
This thesis presents the design, construction and testing of a boundary layer turbine, also known as a Tesla Turbine. A turbine, with discs of 92mm in diameter, central exhaust, plenum chamber, and swappable nozzles was constructed. The setup included instrumentation and a simple torque sensor with which to sense the relatively low torques given the low testing pressures. After construction, the setup was tested with various angles of nozzles ranging from 2.5° to 45° from tangential. The testing resulted in an estimated maximum efficiency of 8.5%, while running the rig at 3 bar, which is comparable to the literature. Unexpectedly, this maximum was achieved with a nozzle pointed at 45° from tangential, which may have been caused by the disc pack variant used in the tests.
The distance analysis of a mine scale event
(2022-02-25) Ollila, Benjamin
Mining induced seismic events greater then Nuttli Magnitude 3.0 are difficult to understand, have high potential consequences and are becoming increasingly common in Canada. The term mine scale event (MSE) is used to describe a seismic event in which the mechanisms and processes involved take place on a scale similar to that of the mine. A MSE from Nickel Rim South Mine was investigated using seismic data to explain its time, location and large magnitude. A novel tool, Time Distance Analysis was developed to identify spatial-temporal trends in seismicity around the MSE. Guidelines were developed to account for the unknown spatial and temporal extent of the processes that led to and were affected by the MSE. The results showed that preceding seismicity tended to coalesce around the eventual hypocenter of the MSE while subsequent seismicity migrated away. The coalescence was interpreted to represent the deterioration of a fault asperity, leading to an eventual rupture. After the MSE occurred, the dispersion of seismicity was interpreted to represent an unloading of the source region.
Electrolytic destruction of cyanide on bare and MNO2 coated 304 stainless steel electrodes
(2021-09-15) Schmidt, Jacob
MnO2 coated lead and ANSI-304 stainless steel anodes were evaluated for use in electrolytic cyanide waste effluent treatment. Cyclic voltametry experiments revealed that MnO2 on lead was too resistive to be a feasible substrate. Cyclic voltammetry on bare and MnO2 coated steel shows evidence of cyanide destruction just prior to the onset of massive oxygen evolution, suggesting a reaction mechanism in which cyanide is oxidized via reaction with hydroxide radical species on the electrode surface. Galvanostatic experiments showed little difference in cyanide oxidation performance behaviour between bare steel and the MnO2 coating. However, copper ion were found to catalyse cyanide oxidation for bare steel, but had no observed effect for MnO2 coated steel. A cost analysis was done comparing electrolytic cyanide destruction using bare steel anodes to the INCO SO2/Air process. Electrolytic cyanide oxidation was concluded to have significantly lower operating costs, but is infeasible due to prohibitive capital costs.
Employing heat pumps to recover low grade industrial thermal resources for space heating and cooling
(2016-05-16) Ross, Ian Michiel
The use of heat pumps to upgrade and recover low grade industrial thermal resources is an opportunity for industry to deliver low cost space heating at a reduced carbon footprint. Heat pumps also offer the potential to provide space heating and space cooling from a single unit. To facilitate rapid determination of the potential for low grade heat recovery using ground source heat pumps, a rapid scoping method was developed capable of establishing critical temperatures to help elucidate which resources are most likely to be recovered economically. To demonstrate the applicability of the rapid scoping method, an analysis of various process cooling waters present at a smelter site was undertaken. The implications for cost and carbon dioxide emissions, were both analyzed for this facility, although the concepts developed can be employed to any site that generates large quantities of thermally low-grade heat.
Energy consumption and GHG emissions at metal mines in Canada and the implications of Canadian climate change polices
(2023-03-08) Smith, Connie
The objectives of this research are to complete a review of energy consumption and greenhouse gas (GHG) emissions at metal mines in Canada, to understand the implication of Canadian climate change legislation for operations at these mines, and to assess practical actions mines can take to reduce their GHG emissions. The mining industry is an energy intensive but profitable industry that plays a critical role in the Canadian economy and the switch to a “green” economy. However, the reliance of the mining industry upon carbon rich fuels, the large and long term land use changes associated with mines sites, and the long life span of mining operations mean that the industry is an important contributor to climate change.
Evaluation of the thermal impact from battery packs from electrical vehicles in underground mining environment
(2019-01-10) de Almeida, Daniel Marques
One of the main aspects which governs the size of ventilation facilities in underground mines is the amount of heat load generated in the underground environment. This heat load comes from many different sources, one of which is the heat contributed by underground diesel machinery operation. One strategy to mitigate the heat and other emissions from such equipment is to substitute these units to similar performance, but more thermally efficient, electric machinery. This study presents a heat load evaluation of the Lithium-iron Phosphate battery system used in a prototype electric mining vehicle. The set of equations which governs the heat generation from these devices have been developed by previous researchers and is used in this thesis to calculate the heat generation and loss. However, in the mining industry, the current methodology for heat load calculation from electric vehicles (EVs) is usually based on the rated power or on a simple power loss equation. This strategy might lead to incorrect estimations of the heat load from this type of machinery. Experimental and simulation work has been conducted as a means to evaluate the heat flux from the Lithium-iron Phosphate battery system. The battery was tested through charging and discharging it under different levels of current within the 10% to 90% range of its maximum capacity. The test was performed firstly with a single cell and then with a module. Furthermore, the battery system was set in operation under different environment temperature settings. These current and temperature levels represent the range of possible conditions in which the prototype will face in service. Through the estimation of the heat released from the other main electrical components in the vehicle, it was possible to calculate the heat impact of these units in the surrounding environment.
Evolution of seismic response and seismic hazard at Goldex Mine’s D1-zone
(2022-10-24) Stratton, Ray
This thesis observes both the evolution of the seismic response and associated seismic hazard at Goldex Mine’s D1-zone over the time period including August 2018 until December 2020. A variety of evaluation methods have been used to discuss the changes in seismic response, the source mechanisms, and the associated hazards. Data visualization and analysis were performed using mXrap software (Australian Centre for Geomechanics). Ultimately, the hazards of the change in seismic response are associated with significant or large seismic events occurring at times well outside of the normal blasting times. Understanding the role that both mining sequence and production constraints plays in the seismic response is key to understanding relative hazards. The change over time as the extraction ratio of the orebody increases is also considered.
Genetic algorithm framework for stochastic open pit mining optimization problems
(2022-09-22) Amponsah, Shadrach Yaw
Genetic algorithm (GA) is a metaheuristic evolution algorithm that has been applied in the area of combinatorial optimization problems. One of these areas of optimization is mine production scheduling. Mine production scheduling is the process of determining the sequence of block extractions over a period of time that will yield the maximum net present value (NPV) for the mining operation subject to a set of constraints. The block extraction sequence needs to occur under certain resource constraints, which presents an NP-hard problem. NP-hard problems are computationally intractable and complex to solve for large- scale problems using exact mathematical models such as Mixed Integer Linear Programming (MILP) and Stochastic Mixed Integer Linear Programming (SMILP). In the mining production scheduling problem, the conventional approach is to use a single interpolated orebody model as the basis for production scheduling. This approach, however, does not consider grade uncertainties. These uncertainties have a significant impact on the NPV and can only be accounted for when modelled as part of the optimization problem. However, modeling these as part of the optimization problem increases the complexities associated with the production scheduling. In this research, a metaheuristic optimization framework based on GA was designed and implemented to solve the NP-hard large-scale open pit production scheduling (OPPS) problem. The problem definition and the resource constraints were formulated and optimized using a specially designed mining-specific GA. A multiple chromosome encoding technique was used in the GA to handle partial block processing to obtain a near-optimal solution. Two case studies from an oil sands dataset were presented in this research. A stochastic formulation (SGA) of the OPPS problem to incorporate grade uncertainty based on equally probable orebody realizations was considered and optimized with the GA framework. A deterministic approach (DGA) to the OPPS problem that did not consider grade variability was also presented. The NPV and computational time from the DGA scenario were compared to a MILP model solved with CPLEX and the SGA scenario was compared to a SMILP model solved with CPLEX as a means to validate and analyze the GA results. There was a 53.6% improvement in the computational time for the DGA compared to the MILP model with CPLEX in Case Study 1. However, the NPV was within 5.1% of the MILP model with CPLEX. The SGA model for Case Study 1 generated an NPV within 5.3% of the NPV of the SMILP model with CPLEX. Conversely, the result of the SGA model was generated in a computational time that was 75.2% better than the SMILP model with CPLEX. For Case Study 2, whereas the MILP model generated NPV of $10,175 M at a gap of 10% after 226 hours, the DGA model generated NPV of $9,142 M at 12.9% gap after 1.3 hours. Additionally, while the SMILP model was at a gap of 101% after 28 days, the SGA model generated NPV of $10,045 M at 10.6% gap after 1.5 hours.
Human detection and face recognition in indoor environment to improve human-robot interaction in assistive and collaborative robots
(2016-10-14) Kunwar, Sumesh
Human detection in indoor environment is essential for Robots working together with humans in collaborative manufacturing environment. Similarly, Human detection is essential for service robots providing service with household chores or helping elderly population with different daily activities. Human detection can be achieved by Human Head detection, as head is the most discriminative part of human. Head detection method can be divided into three types: i) Method based on color mode; ii) Method based on template matching; and iii) Method based on contour detection. Method based on color mode is simple but is error prone. Method based on head template detects head in the image by searching for a template which is similar to head template. On the other hand, Method based on contour detection uses some information to describe head or head and shoulder information. The use of only one criteria may not be sufficient and accuracy of human head detection can be increased by combining the shape and color information. In this thesis, a method of human detection is proposed by combining the head shape and skin color (i.e., Combination of method based on Color mode and method based on Contour detection). Mainly, curvature criteria is used to segment out curves having similar curvature to find human head. Further, skin color is detected to localize face in image plane. A curve represents human head curve if only it has sufficient skin colored pixel in its closed proximity. Thus, by using color and human head curvature it was found that promising results could be obtained in human detection in indoor environment. iv After detecting humans in the surrounding, the next step for the robot could be to identify and recognize them. In this thesis, the use of Gabor filter response on nine points was investigated to identify eight different individuals. This suggests that the Gabor filter on nine points could be applied to identify people in small areas, for example home or small office with less individuals.
In SITU railway track fault detection using railcar vibration
(Laurentian University of Sudbury, 2014-03-17) Pagnutti, Jeffrey L.
This thesis investigates the development of an automated fault detection system developed for a novel lightweight railway material haulage system; in particular, the study aims to detect railway track faults at the incipient stage to determine the feasibility of maintenance decision support, ultimately with the function of preventing catastrophic failure. The proposed approach is an extension of the current state of the art in fault detection of unsteady machinery. The most common railway track faults associated with train derailment were considered; namely, horizontal and transverse crack propagation, mechanical looseness, and railbed washout were the faults of interest. A series of field experiments were conducted to build a database of vibration, speed, and localization data in healthy and faulted states. These data were used to develop, investigate, and validate the effectiveness of various approaches for fault detection. A variety of feature sets and classification approaches were investigated to determine the best overall configuration for the fault detector. The feature sets were used to condense data segments and extract characteristics that were sensitive to damage, but insensitive to healthy variations due to unsteady operation. The pattern recognition classifiers were used to categorize new data members as belonging to the healthy class or faulted class. The fault detection results from the proposed approach were promising. The feasibility of an automated online fault detection system for the lightweight material haulage system examined in this study was confirmed. The conclusions of this research outline the major potential for an iv effective fault detection system and address future work for the practical implementation of this system.
Incorporating cut-off grade optimization and stockpiling into oil sands production scheduling and waste management.
(2017-04-27) Seyed Hosseini, Navid
In achieving maximum benefit in oil sands mining, the long-term production schedule should have the time and sequence of removing ore, dyke material and waste from the final pit limit. An optimum cut-off grade profile and stockpiling will ensure the segregation between these materials meet economic and regulatory requirements. In-pit waste management strategy for oil sands mining requires dyke construction to occur simultaneously with the advancement of mining operations. This research seeks to determine: 1) the optimum life of mine cut-off grade profile and its corresponding tonnages; 2) the time and sequence for removal of ore, dyke material and waste to maximize NPV; 3) the dyke material schedule for dyke construction to minimize construction costs; and 4) the associated impacts of stockpiling and stockpile reclamation with limited time duration. Cut-off grade optimization was used to generate an optimum grade schedule which specifies the cut-off grade, duration of mining of the grade and tonnage mined during the mine life. A heuristic framework, referred to as the Integrated Cut-Off Grade Optimization (ICOGO) model was developed in this research. It generates an optimum cut-off grade policy and a schedule for mining ore and waste, as well as overburden, interburden and tailings coarse sand dyke material for long-term production planning. Subsequently, a mathematical programming framework based on Mixed Integer Linear Goal Programming (MILGP) model was developed to generate a detailed production schedule for removal of ore, waste and dyke materials from the final pit limit. Stockpiling scenarios investigated during the study include: i) no stockpiling; ii) stockpiling and reclaiming at the end of mine life; and iii) stockpiling for one year or two years prior to reclamation. The developed models were applied to two oil sands case studies to maximize the Net Present Value (NPV) of the operations. In both case studies, the NPV generated by the ICOGO model for one year stockpiling scenario was higher than other stockpiling scenarios. For the MILGP the NPV generated for the two year stockpiling scenario was higher than the one year stockpiling scenario. In comparison, whereas the ICOGO model solved the optimization problem faster, the MILGP model results provide detailed mining-cut extraction sequencing for mining.
Incorporating grade uncertainty in oil sands mine planning and waste management using stochastic programming
(2020-02-12) Mbadozie, Obinna
The primary purpose of oil sands mine planning and waste management is to provide ore from the mine pit to the processing plant while containing the tailings in an efficient manner in-pit. Incorporating waste management in the mine plan is essential in maximizing the economic potential of the mineral resource and minimizing waste management costs. However, spatial variability such as grade uncertainty results in ore tonnage variations, which leads to fluctuations in the quantity of ore to be processed and waste to be managed. If grade uncertainty is not incorporated in oil sands mine planning, it may lead to under- or over-design of the waste management system required to support the mining operation, resulting in lost opportunities. Grade uncertainties have profound impact on the Net Present Value (NPV) of the mining project as it may induce large differences between the actual and expected production targets. Thus, the primary research objectives are to develop, implement and verify an integrated oil sands mine planning optimization framework using Stochastic Mixed Integer Linear Programming (SMILP) to integrate the related domains of bitumen grade uncertainty and waste management. The SMILP model determines the order and time of extraction of ore, dyke material and waste that maximizes the Net Present Value (NPV), minimizes waste management cost, and minimizes the geological risk cost of the mining operation. Sequential Gaussian Simulation (SGS) is employed to quantitatively model the spatial variability of bitumen grade in the oil sands deposit. Multiple simulated orebody models are used as inputs for the SMILP model to generate optimal mine plans in the presence of grade uncertainty. MATLAB programming platform was chosen for the SMILP framework implementation. A large-scale optimization solver, IBM CPLEX, is used for this research. To validate the SMILP model, an oil sands case study was implemented based on SGS realizations block models to generate a stochastic integrated production schedule (SMILP schedule), and the results compared with a conventional production scheduling approach based on Ordinary Kriging block model (OK schedule) and E-type block model (E-type schedule). The E-type block model is the average block model of the SGS realizations. In comparison, the SMILP schedule which was based on the developed SMILP framework generated an uncertainty-based integrated production schedule and waste management plan with better financial profitability compared to the OK and E-type schedules. Additional numerical experiments and analysis was done by applying the three schedule results to each of three randomly selected realizations. The corresponding SMILP schedules generated from the realizations were consistently uniform and smooth compared to similar OK and E-type realization schedules. The SMILP framework accounts for geological risk by placing higher penalties for ore grade and ore tonnage deviations from production targets in the early years of mine life to defer production deviations to later years when more geological information becomes available to update the block model and mine plan. By deferring geological risk to later years, the risk of not reaching production targets in the earlier years is minimized, thus creating a smoother and stable production schedule. The results demonstrate that the SMILP schedule generates 14% and 17% improvements in NPV compared to the E-type and OK schedules respectively. These results prove that the SMILP model is a useful tool for optimizing stochastic integrated oil sands production schedules whilst taking into account grade uncertainty.
Interpretation of rock mass yield using apparent stress of microseismic events – examples from Glencore’s Nickel Rim South Mine, Sudbury, Ontario
(2018-05-11) Carusone, Oliver Thomas Sousa
Seismic events are manifestations of sudden, inelastic deformations in a rock mass. The characteristics of these deformations are reflected in quantitative descriptors of seismic events, known as seismic source parameters. The seismic source parameter apparent stress (σa) is a relative estimate of co-seismic stress change. This parameter has been used by other authors to infer local stress conditions in a rock mass and how they vary in space and time. This thesis investigates short term space-time variations in apparent stress in spatially-isolated volumes of a rock mass following open stope blasts. The results are used to infer how the new excavation affects the nearby rock mass. These excavations are expected to cause local stress increases as stress redistributes around the void, and stress decreases as rock mass near the excavation yields and sheds stress. Data for this research is taken from Glencore’s Nickel Rim South Mine (NRSM) in Sudbury, Ontario. This modern operation has a state-of-the-art microseismic monitoring array that consistently locates events with less than 5 m of residual error and provides accurate source parameter estimates for large and small events. NRSM uses a bulk open stoping mining method, which creates large excavations on the order of several thousand tonnes in a matter of a few seconds. The large stress changes and loss of confinement produced by these blasts can generate large seismic responses which provide an abundance of information about rock mass behaviour. Analysis of apparent stress over time is performed spatially isolating a group of events and tracking apparent stress variation in a moving window. This analysis shows that apparent stress: • Rapidly increases for a matter of minutes immediately following the blast. • Gradually decreases for a matter of hours to a lower level than before the blast. • Slowly increases over a matter of days to weeks. Based on the mechanics of rock masses near excavations and use of apparent stress to infer local stress conditions, these variations are interpreted to correspond with: • Mining-induced stress increasing with the creation of a new excavation. • Stress decreasing as the rock mass near the stope yields and/or enters its post-peak strength. • Stress increasing farther from the stope as a result of the more damaged rock mass closer to the stope shedding stress onto less damaged regions. Variations in event-stope distances are also analysed to re-enforce the inferences made based on the variations in apparent stress over time. The analysis of event-stope distances shows that events: • With high apparent stress tend to locate farther from the stopes than events with low apparent stress. • Initially move away from the stopes for a matter of hours after the blast. • Gradually move back towards the stopes for a matter of hours to days. • Gradually move away from the stopes again for a matter of days to weeks. The inferred rock mass behaviour based on these variations are: • Higher stress conditions in more confined and less damaged regions of the rock mass. • Stress redistributing around the new excavation and creating a new zone of active rock mass yield. • Yield occurring in a more consistent region of the rock mass as redistribution of stress outside the more damaged regions slows. • Growth of damaged zones as rock mass yield progresses over time These observed variations and inferred behaviour are used to propose a conceptual model for rock mass yield which describes the formation of an excavation damage zone following a blast. Further study based on this research may use more detailed aspects of the variations to calibrate constitutive behaviour of rock masses (making it a useful tool for numerical model calibration), or relate variations in apparent stress to the occurrence of large events (making it a useful tool for seismic hazard forecasting).

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