Download or read book GLOBAL OPTIMIZATION OF THE OPEN PIT MINING COMPLEX WITH INTEGRATED CUT OFF GRADE OPTIMIZATION UNDER UNCERTAINTY written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract : The mining complex refers to an integrated problem where the material is extracted from the mines; the extracted material is passed through a series of processing facilities connected with various material handling methods to generate a set of finished products, which can be sold to the customers. The optimization of the mining complex refers to the simultaneous optimization of the multiple mine production schedules, the destination of the materials, and the method of processing throughout the life of the project. The purpose of optimizing the mining complex is to deal with the effective management of resources and maximize cash flows to generate higher profits over the life of the project. The goal of this dissertation is to develop a global optimization methodology that integrates geological (supply) uncertainty and can manage the risk in the design, mining complex operations, and maximize the cash flows. In this study, a new production schedule approach is presented that integrates geological uncertainty and generate the extraction sequence for the mining complex problem. The extraction sequence is developed to maximize the net present value and provide a consistent quantity of the material to different destinations. To optimize the quantity of materials sent to different destinations, the destination policies are defined based on the cut-off grade optimization and block economic values. This allows to form the destination policies for the mined material into various processing streams and maximize the value of the operation. The production schedule and the destination policies are optimized within a unified solution approach for the mining complex problem. The work presented advances the field through the development of the new model that uses the combination of maximum flow, genetic algorithm, and Lane's method for the global optimization of the mining complex. The method simultaneously optimizes the production schedule and the cut-off grade while considering uncertainty. The performance advantages and limitations are analyzed and tested on real-world examples. The results show that the models reduce the production risks and increase the net present value of the mining operation.
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 On Globally Optimizing a Mining Complex Under Supply Uncertainty written by Luis Montiel Petro and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mining complexes are generally comprised of multiple deposits that contain several material types and grade elements, which are transformed in available processing destinations and transported to final stocks or ports as saleable products. These components, associated with a mining complex, encompass multiple sequential activities: (i) Mining the material from one or multiple sources; (ii) blending the material including stockpiling; (iii) transforming the material in different processing destinations considering operating modes; (iv) transporting the transformed material to final stocks or ports. Since these activities are strongly interrelated, their optimization must take place simultaneously. Conventional mining optimization methods suffer from at least one of the following drawbacks when optimizing mining complexes: some decisions are assumed when they should be dynamic (operating modes, destination of mining blocks, etc.); component based objectives are imposed, which might not coincide with global objectives; many parameters are assumed to be known when they are uncertain. Past research works have demonstrated that geological uncertainty is the main cause of the inability of meeting production targets in mining projects. This thesis presents methods to optimize mining complexes that simultaneously consider different components and account for geological uncertainty. A multistage methodology that uses simulated annealing algorithm to generate risk-based production schedules in mining complexes with multiple processing destinations is presented and implemented in Escondida Norte (Chile) copper dataset. Its implementation using Escondida Norte dataset generates expected average deviations of less than 5% regarding mill and waste targets, whereas a mine production schedule generated conventionally over a single estimated model generates expected average deviations of 20 and 12% for mill and waste targets respectively. An iterative improvement algorithm that considers operating modes at different processing destinations is developed and applied to a copper complex. The objective function seeks for maximizing discounted profits along the different periods and scenarios (orebody simulations). The implementation of the method at a copper deposit allows reducing the expected average deviations from 9 to 0.2% regarding the capacity of the first process while increasing the expected NPV by 30% when compared with an initial solution generated conventionally. A method that uses simulated annealing at different decision levels (mining, processing and transportation) is described and tested in a multipit copper operation. The implementation of the method in a multipit copper operation permits the reduction of the expected average deviations from the capacities at two mills from 18-22% to 1-3% and the expected average deviation from the targets regarding two blending elements from 7-1.8% to 0.3-0.6% when compared to an initial solution generated conventionally. The expected NPV also improves by 5%. The previous method is extended to mining complexes that combine open pit and underground operations and it is tested in a gold complex in Nevada. The implementation of the method at Twin Creeks gold complex in Nevada shows improvements in meeting the metallurgical blending requirements while increasing the expected NPV by 14%. The formulations described in this thesis encompass a large number of integer variables given the discretization of the mineral deposits. To solve the problems, efficient optimization algorithms are implemented with significant improvements when compared with conventional deterministic approaches. These algorithms outperform conventional methods regarding expected NPV and meeting targets at the different components of the value chain." --
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 Global Asset Optimization of Open Pit Mining Complexes Under Uncertainty written by Ryan Goodfellow and published by . This book was released on 2014 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Dynamic Optimization of Cut off Grade in Open Pit Mines written by Drew Barr and published by . This book was released on 2012 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mining operations exploit mineral deposits, processing a portion of the extracted material to produce salable products. The concentration of valuable commodities within these deposits, or the grade, is heterogeneous. Not all material has sufficiently high grades to economically justify processing. Cut-off grade is the lowest grade at which material is considered ore and is processed to create a concentrated commodity product. The choice of cut-off grade at a mining project can be varied over time and dramatically impacts both the operation of the mine and the economics of the project. The majority of literature and the accepted industry practices focus on optimizing cut-off grade under known commodity prices. However, most mining operations sell their products into highly competitive global markets, which exhibit volatile commodity prices. Making planning decisions assuming that a given commodity price prediction is accurate can lead to sub-optimal cut-off grade strategies and inaccurate valuations. Some academic investigations have been conducted to optimize cut-off grade under stochastic or uncertain price conditions. These works made large simplifications in order to facilitate the computation of a solution. These simplifications mean that detailed mine planning data cannot be used and the complexities involved in many real world projects cannot be considered. A new method for optimizing cut-off grade under stochastic or uncertain prices is outlined and demonstrated. The model presented makes use of theory from the field of Real Options and is designed to incorporate real mine planning data. The model introduces two key innovations. The first is the method in which it handles the cut-off grade determination. The second innovation is the use of a stochastic price model of the entire futures curve and not simply a stocastic spot price model. The model is applied to two cases. The first uses public data from a National Instrument 43-101 report. The second case uses highly detailed, confidential data, provided by a mining company from one of their operating mines.
Download or read book Long term Mine Planning in Presence of Grade Uncertainty written by Behrang Koushavand and published by . This book was released on 2014 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Open-pit mining is widely used to extract natural resources. Low cut-off grades and large operations can make open-pit mining profitable. An important challenge is to determine the optimum production schedule. Usually the goal is to maximize the net present value of the project while delivering ore to the plant at full capacity. The best production plan would require complete knowledge of the orebody and all other engineering and economic parameters. An estimated block model is often used to determine the production schedule. Uncertainty is inevitable with widely spaced drill holes. The open-pit production schedule based on estimated models may be suboptimal and affected dramatically by grade uncertainty. The research documented herein develops, implements and verifies four mixed integer optimization frameworks for long-term production scheduling in the presence of grade uncertainty. The main contributions of this research are (1) consideration of cost of grade uncertainty to influence the production plan, (2) accounting for the linear and nonlinear effects of the grade uncertainty on the long-term mine planning, (3) development of a mixed integer linear programming model that maximizes NPV and minimizes the cost of the grade uncertainty by considering a stockpile, and finally (4) implementation of a quadratic optimization model accounts for grade uncertainty in the long-term production plan.
Download or read book Stochastic Global Optimization of Open Pit Mining Complexes with Capital Expenditures written by Ryan Goodfellow and published by . This book was released on 2015 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Economic Assessment and Mine Production Optimization of an Open pit Gold Mine Operation in Peru Based on the Iterative Cutoff Grade Analysis Approach written by Bruno Muncher Ricketts and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Surface mining operations involve high levels of complexity and uncertainty that last for many years and require huge capital investment and risk. Each open-pit mine is unique, based on the physical characteristics of the ore deposit and on the operational parameters of the extraction method; therefore, the most profitable way to exploit a mineral deposit requires considerable evaluation and planning. However, all operations share the same priorities, the maximization of the return on the investment and the maximization of the recovery of the resource. Both are linked to the optimization of profits, which in mineral operations is done by optimizing the ore cutoff grade, considering the block model geometry. The Coriorcco Gold Project refers to an open-pit mining operation at pre-feasibility stage located at about 4100 meters above sea level in the Peruvian Andes. This mining project is currently owned by the company Management Environmental Solutions (MESSA) and is intended to begin operations before the year 2019. To have a better understanding of the project, a general description and a technical overview of the main parameters related to the development will be addressed, including, but not limited to: the open-pit design, production rate, tailing facility construction, haul road construction, blasting design, and material handling equipment selection. The present study is intended to develop the economic assessment and mine production optimization of the Coriorcco Gold Project, based on the iterative cutoff grade analysis approach. This approach represents a win-win situation for all major players in the mining industry. The company benefits from better economic results due to a 40.79% higher Net Present Value (NPV) and 24.5 % higher Internal Rate of Return (IRR). The government and nearby communities benefit from a smaller environmental and social impact, as an optimized cutoff grade reduces the mine life from 23.25 to 15.73 years, and therefore, the presence of the company in the region. Furthermore, the economic viability of the project will be thoroughly analyzed in distinct operational and economic scenarios. Three different sensitivity analysis regarding alternative values of processing capacities, gold prices and dilution rates will be evaluated. Finally, results will be analyzed and discussed, revealing the advantages and disadvantages of the optimization method, as well as the economic impact that a change in these variables could cause.
Download or read book The Optimization of Mine Planning Aspects Under Uncertainty written by Rein Dirkx and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mining operations typically face critical operational decisions based on uncertain information. This uncertainty is inherent to the mining process and cannot be overcome, as materials have to be extracted from underground, which can never be fully explored. This thesis addresses two pertinent aspects of many mining operations while directly incorporating this inherent uncertainty into the optimization. The uncertainty is used to our advantage by minimizing the resulting downside risk while maximizing the upside potential. The first aspect, addressed in Chapter 2, is the optimization of infill drilling schemes, a decision faced by every single mining operation on various scales. The second aspect, addressed in Chapter 3, focuses on the stochastic optimization of a production schedule of a block caving operation, a popular mass mining alternative to open pit mines. The optimization of infill drilling is based on a multi-armed bandit (MAB) framework. The novelty of this approach is the application of an advanced machine learning method like MAB to find an elegant solution to the infill drilling problem. The method is applied to a case study of a gold mining complex. The main issue in this mining complex is the uncertainty in their long-term, multi-element stockpiles on which the infill drilling optimization is performed. Stockpiles are often very variable, but their uncertainty can be quantified using conventional stochastic orebody modelling. Although the infill drilling optimization is applied to a stockpile, the proposed method is more general and can be applied to any deposit. The approach proposed in Chapter 3 is the first stochastic optimization approach for scheduling a block cave mine that explicitly includes grade and hang-up uncertainty into the optimization. Hang-up uncertainty is defined as the uncertainty related to ore that clogs the draw points due to aberrant fracturing. The grade uncertainty is incorporated via stochastic orebody simulations, similar to what has been employed for open pit operations in the past, while hang-up uncertainty, the main contribution of this work, is incorporated by tracking and minimizing the delays caused by hang-ups over multiple scenarios. The results of the case study show a reduction of the annual overtime incurred due to delays of 95 % when the hang-up uncertainty is included in the optimization compared to when hang-ups are ignored." --
Download or read book Cut off Grades and Optimising the Strategic Mine Plan written by Brian Hall and published by Spectrum. This book was released on 2019-08-05 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth look at an integral part of mining strategy optimisation - cut-off specification.
Download or read book Handbook of Operations Research in Natural Resources written by Andres Weintraub and published by Springer Science & Business Media. This book was released on 2007-09-19 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is the first systematic handbook treatment of quantitative modeling natural resource problems, their allocated efficient use, and societal and economic impact. Andrés Weintraub is the very top person in Natural Resource research. He has selected co-editors who are at the top of the sub-fields in natural resources: agriculture, fisheries, forestry, and mining. The book covers these areas with contributions from researchers on, among others, modeling natural research problems, quantifying data, and developing algorithms.
Download or read book Constraint Integer Programming written by Tobias Achterberg and published by . This book was released on 2008 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Dynamic Mid term Optimization of a Mining Complex Under Uncertainty written by Maria Fernanda Del Castillo 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 Advances in Spatio Temporal Analysis written by Xinming Tang and published by CRC Press. This book was released on 2007-08-23 with total page 1321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments in Geographic Information Technology have raised the expectations of users. A static map is no longer enough; there is now demand for a dynamic representation. Time is of great importance when operating on real world geographical phenomena, especially when these are dynamic. Researchers in the field of Temporal Geographical Information Systems (TGIS) have been developing methods of incorporating time into geographical information systems. Spatio-temporal analysis embodies spatial modelling, spatio-temporal modelling and spatial reasoning and data mining. Advances in Spatio-Temporal Analysis contributes to the field of spatio-temporal analysis, presenting innovative ideas and examples that reflect current progress and achievements.
