Download or read book Adaptive Simultaneous Stochastic Optimization of a Gold Mining Complex a Case Study written by Zachary Levinson and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Study of Simultaneous Stochastic Optimization of Open Pit Mining Complexes written by Ziad Saliba and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Over the last several years advances in the field of mine planning have led to the development of cutting-edge simultaneous stochastic optimization frameworks for mining complexes. The latest methods consider mining operations as a resource-to-market integrated mineral value that transforms raw in-situ materials into sellable products, a mining complex. Simultaneous stochastic optimization frameworks make use of a paradigm shift that considers the value of the sellable products, as opposed to economic block values, to drive the optimization process and capitalize on the synergies between the central, interrelated components of a mining complex. These methods maximize the value of mining operations and manage technical risk by incorporating uncertainty directly into unified optimization formulations. This thesis studies the simultaneous stochastic optimization framework through two real-world case studies, applying the methods and assessing their characteristics and limitations. The second chapter of this thesis presents an application of a stochastic framework that simultaneously optimizes mining, destination and processing decisions for a multi-pit, multi-processor gold mining complex with challenging geochemical processing constraints. The framework accounts for supply and market uncertainty via stochastic orebody and commodity price simulations as inputs to a unified optimization model. The case study notably assesses the impacts of integrating market uncertainty as input that influences all components of the production schedule. Additionally, cut-off grade decisions are determined by the simultaneous optimization process, considering material variability and operating constraints while reducing the number of a-priori decisions to be made. This approach generates solutions that capitalize on the synergies between extraction sequencing, cut-off grade optimization, blending and processing while managing and quantifying risk in strategic plans. Which ultimately leads to more metal production and higher NPVs than traditional methods. The third chapter applies an extension of the generalized simultaneous stochastic optimization formulation that considers capital expenditure (CapEx) options as part of the life-of-asset planning process. Enabling the case study to consider environmental issues relating to tailings management and model a tailings facility expansion. The application at a multi-element open pit mining complex simultaneously optimizes the extraction sequence, cut-off grades, and downstream decisions from two open-pits with a set of stockpiling options, an autoclave and a tailings storage facility. The project bottleneck is the tailings facility volume because it stores both process tails, and potentially acid-generating waste rock from the mines. Results show that, when given the option, the optimizer chooses to make a significant CapEx investment to expand the tailings storage facility 25% by volume. This expansion allows for a meaningful expansion of both pit limits, 40% by mass, resulting in an extended metal production and revenue generation horizon that yields 14% more gold ounces and a 4% improvement in NPV for the mining complex. The framework provides decision makers with a realistic evaluation of the investment's impact on the mining complex." --
Download or read book An Application of Simultaneous Stochastic Optimization in Mining Complexes and Integrating Mine to port Transportation written by Mélanie LaRoche-Boisvert and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mineral value chain or mining complex is an integrated system representing all components of a mining operation for the extraction, transportation and transformation of material, from sources (open pit and underground mines) to customers or the spot market. Simultaneous stochastic optimization aims to optimize all components of a mineral value chain, including extraction schedules for the mines, stockpile management, processing and transportation scheduling, jointly to capitalize on the synergies that exist within the system. Additionally, the simultaneous stochastic optimization approach incorporates material supply or geological uncertainty using equally probable geostatistical (stochastic) simulations of the attributes of interest of the deposits. The incorporation of material supply uncertainty allows the approach to manage the related major technical risks.The first contribution of this thesis is the application of simultaneous stochastic optimization at a three-mine open pit gold mining complex, incorporating material supply uncertainty using stochastic simulations of the gold grades of each deposit. The case study maximizes the net present value of the operation by generating life-of-mine schedules for each deposit considered and stockpile management plans, which maximize gold production and minimize the associated costs. The study also assesses the impacts of material hardness on the processing facilities, notably the SAG mill, and the recovered gold. This assessment indicates that the SAG mill is the bottleneck of the operation; due to the lack of availability of soft material in the considered deposits, the throughput of material at the SAG mill is significantly lowered. The second contribution of this thesis is a new stochastic mathematical programming formulation jointly optimizing long-term extraction scheduling and mine-to-port transportation scheduling for mining complexes under supply uncertainty. Mine-to-port transportation systems represent an important component of certain mining complexes, such as iron ore mining complexes, ensuring that extracted products reach their intended clients. This component of the mineral value chain has not been included in previous simultaneous stochastic optimization formulations, ignoring the interactions between the transportation system and the other components of the mining complex. The proposed model simultaneously optimizes extraction scheduling, stockpile management, mine-to-port transportation scheduling and blending under material supply uncertainty. It aims to minimize the costs associated with meeting quantity and quality demand for the products at the port, managing the risks associated with the material supply uncertainty using stochastic simulations of grades. The model is applied to an iron ore mining complex consisting of two open pit mines, each with a waste dump, a stockpile and a loading area, connected to a single port by a railway system. Material is transported by two trains. At the port, demand for two products are considered, each with quality constraints relating to five elements. Stochastic simulations of the five elements considered are used to represent the material supply uncertainty. By optimizing the extraction and the mine-to-port transportation jointly, the case study is able to determine that only the first train is necessary to transport material to meet demand at the port for the first three years of mine life; for the remainder, the second train is also needed. As such, the second train could be allocated to another operation for better use during the first three years of operation or its purchase could be delayed. The model provides decision makers with a realistic use of the mine-to-port transportation system"--
Download or read book High order Simulation of Geological Domains of a Gold Deposit and Its Effects on the Simultaneous Stochastic Optimization of a Mining Complex written by Daniel Morales and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In the last decade, strategic mine planning has evolved into a framework that simultaneously optimizes decisions of a mining complex, while considering different sources of uncertainty. A typically overlooked source of uncertainty corresponds to the volumes and boundaries of geological domains. Geological domains correspond to different kinds of materials defined by respective chemical or physical properties, such as ore and waste, oxides and sulphurs, or different lithologies. Along with their spatial distribution, geological domains can affect destination policies, recoveries, production, and finally, financial forecasts. The case study presented here quantitively measures the effects of simulated geological domains in the simultaneous stochastic optimization of a gold mining complex.Geological domains are traditionally modelled through wireframes made by experts, reflecting their best interpretation of available sparse data, while ignoring uncertainty and local variability. Categorical attributes are used to model geological domains, and their stochastic simulation accounts for uncertainty and reproduction of local variability. The ability of two-points simulation methods to reproduce complex patterns or the requirement of a training image in multiple-points simulation methods, have limited their implementation in mining environments. High-order simulation of categorical attributes presents a mathematically consistent framework that overcomes the mentioned limitations by using high-order spatial statistics from sample data and avoiding the requirement of the training image. The high-order simulation method allows obtaining equally probable realizations of geological domains in real life-sized mineral deposits.The case study at a gold mining complex shows two stochastic mine plans based on two sets of geological realizations respectively. Geological domains of the first set are modelled using conventional wireframes while in the second set, domains are simulated through the high-order method. Gold grades are simulated inside geological domains for both sets. The resulting mine plans are substantially different. While both plans present a similar quantity of metal recovered and years of lifespan, risk profiles are up to 40% wider, and the expected NPV is 20% higher for the case of simulated geological domains. These results stress the importance of considering the uncertainty related to geological domains to develop and optimize strategic mine plans"--
Download or read book Simultaneous Stochastic Optimization of an Open Pit Gold Mining Complex with Supply and Market Uncertainty written by Ziad Saliba and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High order Direct Block Support Simulation and Application at a Gold Mining Complex written by Joa̳o Pedro de Carvalho and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Over recent years, new methods have developed the mining production schedule stochastic optimization into a framework that includes, in one mathematical formulation, all the components of a mining complex and optimizes it simultaneously. A mining complex is a set of operations that integrate all aspects in a mineral value chain, starting from the materials extracted from the ground culminating with its transformations into a final product delivered to the mineral market. The framework diverges from past methods that optimize each operation of the mining complex separately, which do not benefit from the coexisting harmony between connected processors. Core inputs of this all-inclusive optimization are the geostatistical simulations quantifying variability and uncertainty of relevant attributes in a given mineral deposit. To date, the state-of-the-art simulation methods can reproduce complex geometries and multi-point connectivity of extreme values. However, the generated realizations are performed at the point-support which requires a post-processing step to generate block-support orebody models, as needed to represent the mineral deposit due to engineering purposes. For example, a multimillion block model requires discretization of the magnitude of hundreds of millions of nodes to simulate. This presents computational challenges in post-processing such a massive model. The first part of this thesis presents the high-order simulation method that generates realizations directly at the block support conditioned to the available data at point support scale. Following the sequential simulation paradigm, the method estimates, at each block location, the cross-support joint probability density function using Legendre-like splines as the set of basis functions needed. The previously simulated blocks are added to the set of conditioning data, which initially contains the available drillhole data. A spatial template, defined by the configuration of the block to be simulated and related conditioning values in both support scales, is used to infer additional high-order statistics from a training image. First, the method is tested in a controlled environment, and the simulated realizations show consistent results reproducing major structures and high-order relations of data. Second, the method is used to simulate a gold deposit, and its efficiency is demonstrated by reproducing spatial statistics up to a fourth-order, coinciding with the ones present in the available drillhole data. The running time of generating one realization with the proposed approach is reduced by a factor of 5 when compared to the point-support version of the algorithm.The second part of the thesis presents a case study where the simulations of the gold deposit mentioned above are incorporated into the simultaneous optimization of a gold mining complex. The resulting life-of-mine (LOM) production schedule yields 5 to 16% higher net present value when compared to the case, where the same mining complex is optimized, but the deposit is modelled through a traditional simulation method based on two-points statistics. The comparison shows that incorporating simulations with more realistic connectivities of high-grade blocks, through the use of high-order direct block simulations, into the optimization results in a more informed LOM production schedule. This shows that the optimization can capitalize on the better understanding of the connectivity of high-grades." --
Download or read book Simultaneous Stochastic Optimization written by Zachary Levinson and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mining complex is a fully integrated logistics network that represents the transportation and transformation of material from the source, open-pit and underground mines, to the customers and/or the spot market. Mining enterprises around the world aim to create a strategic mine plan for each of their assets that maximizes the value generated for a company and its stakeholders. Simultaneous stochastic optimization is used to generate a production schedule that defines the extraction sequence, stockpiling, processing, blending, capital investment and waste management decisions under supply uncertainty. The optimization approach exploits synergies within the mining complex by considering the contribution of each interconnected component in a single mathematical formulation. These components may include multiple mines, processors, stockpiles, waste facilities, and methods of transportation. In this thesis, a study of simultaneous stochastic optimization is completed in two operating gold mining complexes focusing primarily on the integration of waste management and capital investment decisions under supply uncertainty.The first application presents the simultaneous stochastic optimization of a gold mining complex focusing on waste management, particularly the uncertain aspects of acid generating waste. Typically, when optimizing the production schedule, the primary focus is to deliver valuable products to the market. However, this tends to ignore the environmental and economic impact of simplifying waste management requirements, including the storage and disposal of waste material. Stricter regulations and engineering requirements are transforming past mining practices to develop more sustainable operations. These transformations increase the financial cost of waste management and identify the requirement to integrate waste management into the production schedule. Additionally, misrepresenting the material uncertainty and variability associated with the amount of waste produced can impact, both, the stakeholders and the profitability of a mining complex. In this case study, a simultaneous stochastic optimization approach is applied to generate a long-term production schedule that considers waste management. The resulting schedule leads to a 6% increase in the net present value when compared to a conventional approach, while minimizing the likelihood of deviating from production targets and ensuring permit constraints are satisfied. Second, an innovative strategic mine planning approach is applied to a multi-mine and multi-process gold mining complex that simultaneously considers feasible capital investment alternatives and capacity management decisions that a mining enterprise may undertake. The simultaneous stochastic optimization framework determines the extraction sequence, stockpiling, processing stream, blending, waste management and capital investment decisions in a single mathematical model. A production schedule branches and adapts to uncertainty based on the likelihood of purchasing a feasible investment alternative that may increase mill throughput, acid consumption, and tailings capacity. Additionally, the mining rate is determined simultaneously by selecting the number of trucks and shovels required to maximize the value of the operation. The mining complex contains several sources – two open-pit gold mines and externally sourced ore material – stockpiles, waste dumps, tailings and three different processing streams. The simultaneous optimization framework integrates the blending of sulphates, carbonates, and organic carbon at the autoclave for refractory ore while managing acid consumption. The resulting production schedule indicates an increase in net present value as the optimization model adapts to uncertainty and manages the technical risk of capital investment decisions"--
Download or read book Adaptive Simultaneous Stochastic Optimization of Miningcomplexes where is the Value Coming From written by Maria Fernanda del Castillo and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Simultaneous Stochastic Optimization of Production Scheduling at Twin Creeks Mining Complex Nevada written by Luis Montiel and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Two stage Stochastic Optimization of the Escondida Mining Complex Chile written by Maria Fernanda Del Castillo and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Simultaneous Short term Decision making in Mining Complexes Integrating Geometallurgy Assisted by Production Data written by Christian Both and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mining complex is an integrated business of mines and downstream facilities that extracts raw materials, converts extracted materials into sellable products, and transports products to markets and customers. Conventionally, individual components of a mining complex are optimized independently of each other, which causes underperformance of the mineral value chain. Simultaneous stochastic optimization of mining complexes has shown to create strategic mine plans that increase the net present value while reducing risk of meeting production targets by incorporating geological and price uncertainty. While these developments jointly optimize strategic decisions of a mining complex, short-term planning makes weekly to monthly decisions to best meet long-term production targets and maximize value. These decisions include short-term extraction sequence, destination of materials, and downstream material flow in mining complexes. Furthermore, the optimal allocation of the mining fleet is an important aspect of short-term planning; however, the joint stochastic optimization of short-term production schedules and fleet management in mining complexes has not yet been developed. Additionally, geometallurgical properties that drive revenues, costs, and the ability to meet production targets, are not integrated in the optimization of short-term production schedules in mining complexes. This thesis expands the simultaneous stochastic optimization of mining complexes for long-term planning into a decision-making framework for short-term mine planning through the incorporation of fleet management and geometallurgical prediction models of plant performances into the short-term optimization of mining complexes, which is assisted by the utilization of collected datasets from production processes in mines and processing plants. First, a new stochastic integer programming model for short-term planning is developed that extends the simultaneous stochastic optimization of mining complexes to allow the scheduling of a heterogeneous truck fleet and shovel allocations while considering the costs and loss of production caused by shovel relocation. Next to geological uncertainty, equipment performance uncertainties related to production rates, availabilities, and truck cycle times are integrated. Next, a geometallurgical model for the prediction of ball mill throughput in mining complexes is developed which utilizes drilling penetration rates and recorded throughput rates of the operating plant. The creation of hardness proportions avoids biases introduced by the change of support and blending of non-additive geometallurgical properties. By integrating the throughput prediction model into the simultaneous stochastic optimization formulation, planned production can be achieved reliably because scheduled materials match with the predicted mill performance. The throughput prediction model is extended thereafter by including recorded measurements of ball mill power draw and particle size distributions. Since the addition of new features increases the possibilities of non-linearities, a neural network is used. The prediction of metallurgical responses of the operating plant and their incorporation into short-term stochastic production scheduling is finally extended by creating prediction models of consumption rates of reagents and consumables in a gold mining complex. With the new developments presented in this thesis, the simultaneous stochastic optimization of mining complexes can now be applied for short-term planning, modelling the operational aspects of the mining fleet and metallurgical behaviour of processing plants in greater detail. The integration of these short-term aspects leads to short-term mine plans that are more likely to align with long-term production targets while benefitting from synergistic effects that maximize the profit of the mineral value chain"--
Download or read book Expanding Simultaneous Stochastic Optimization of Mining Complexes to Introduce Geometallurgical Constraints Application at the Escondida Mining Complex Chile written by Ashish Kumar and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ore Reserve Estimation and Strategic Mine Planning written by Roussos Dimitrakopoulos and published by Springer. This book was released on 2015-11-15 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mining business faces continual risks in producing metals and raw materials under fluctuating market demand. At the same time, the greatest uncertainty driving the risk and profitability of mining investments is the geological variability of mineral deposits. This supply uncertainty affects the prediction of economic value from the initial valuation of a mining project through mine planning, design and production scheduling. This book is the first of its kind, presenting state-of-the-art stochastic simulation and optimization techniques and step-by-step case studies. Quantification of geological uncertainty through new efficient conditional simulation techniques for large deposits, integration of uncertainty to stochastic optimization formulations for design and production scheduling and the concurrent management of risk are shown to create flexibility, options and oportunities, increase asset value, cashflows and return on investment. New approaches introduced include resource/reserve risk quantification, cost-effective drilling programs, pit design and long-term production scheduling optimization with simulated orebodies, ore reserve classification, geologic risk discounting, waste managing and demand driven scheduling, risk assessment in meeting project production schedules ahead of mining, risk based optimal stope design, options valuation when mining. Applications include commodities such as gold, copper, nickel, iron ore, coal and diamonds.
Download or read book Unifed Modelling and Simultaneous Optimization of Open Pit Mining Complexes with Supply Uncertainty written by Ryan Goodfellow and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "A mining complex is an integrated business that extracts materials from open pit or underground mines, treats extracted materials via a series of processing facilities that are interconnected by various material handling methods, and generates a set of products that are sold and delivered to customers and/or the spot market. The primary objective when optimizing a mining complex is to maximize its value for the business and its stakeholders while obeying the technical constraints that limit production. This optimization is traditionally performed by treating the various components independently, leading to the suboptimal use of the natural resources and financial capital, and the underperformance of the mining complex. The global optimization of mining complexes aims to simultaneously optimize the mine production schedules, which define the distribution of materials over time, the destination policies, which define where extracted materials are sent, and the use of the various processing streams for processing, distribution and product marketing. As the size of the mining complex grows, there is a compounded effect that uncertainty has on the components, and new stochastic optimization methods are needed to manage this risk. This thesis aims to generate a unified modelling and global optimization methodology that integrates supply uncertainty and manages risk in the design and operation of mining complexes, and can be adapted to suit the needs and objectives of individual operations.This work advances the related field of knowledge through the development of new models and methods for optimizing mining complexes with uncertainty, which is achieved through five major contributions. First, a stochastic global optimization method is developed to simultaneously optimize multi-mine production schedules, destination policies, processing streams and capital expenditures for capacity design; while existing state-of-the-art methods may address some of these aspects, they have not been previously integrated in a simultaneous optimization model that does not rely on divvying up the global model into sub-problems. Second, a new, unified modelling approach is developed that permits the proposed methods to be tested on many different types of mining complexes with a high degree of modelling detail; as a result of this unified approach, non-linear relationships can easily be integrated in the optimization models - a limitation of existing deterministic and stochastic methods. Third, and a result of the previous development, a new approach is developed to model the economic value of the products sold, rather than the materials mined. Existing models and methods are limited by the assumption that each block has an economic value, hence the optimal processing stream is known a priori, and the block is treated and sold in isolation from other blocks; in some cases, this may lead to substantially undervaluing the resource. Using the new modelling approach, it is possible to evaluate the economic potential of products at the point of sale, rather than making these unrealistic assumptions at the block-level. Fourth, computationally efficient solvers are adapted and applied using metaheuristics. A combination of particle swarm optimization and a modified simulated annealing algorithm are developed to optimize various aspects of the global optimization problem; these methods have not been previously combined for mine optimization, and requires devising new methods to change designs and ensure that the optimizers do not get trapped in local optima. Finally, the performance, advantages and limitations of the models and methods are analyzed through full-field testing on real-world and large-scale examples. The results consistently reinforce the concept that it is possible to not only reduce the risk of not meeting production targets, thus guaranteeing financial forecasts are met, but also increase the net present value of the operation." --
Download or read book Advances in Applied Strategic Mine Planning written by Roussos Dimitrakopoulos and published by Springer. This book was released on 2018-01-17 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of papers on topics in the field of strategic mine planning, including orebody modeling, mine-planning optimization and the optimization of mining complexes. Elaborating on the state of the art in the field, it describes the latest technologies and related research as well as the applications of a range of related technologies in diverse industrial contexts.
Download or read book Advanced Analytics in Mining Engineering written by Ali Soofastaei and published by Springer Nature. This book was released on 2022-02-23 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.
Download or read book Learning to Schedule Heuristics for the Simultaneous Stochastic Optimization of Mining Complexes written by Yassine Yaakoubi and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
