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Mining operations determine a long-term production schedule, often to maximize net present value. For a time horizon of between years and decades, optimization models seek the extraction times—with monthly or yearly fidelity—of three-dimensional, notional blocks of ore and waste within a deposit to satisfy spatial precedence constraints, as well as resource constraints on the amount of material extracted and sent to the mill. With algorithmic advances, as well as those in mine planning software and in hardware, we are able to solve instances with a decade-long horizon at daily fidelity. The resulting objective, repeatable, and defensible schedules inform production and maintenance supervisory decisions based on resource availability, that is, loaders, shovels, haul trucks, and mineral processors. We implement our solutions at the Turquoise Ridge underground gold mine in Nevada, United States. These solutions indicate more than a 2% increase in total ounces extracted over a decade while decreasing development footage by as much as 11% over the same time horizon. Furthermore, we are able to incorporate rules governing a shared resource and to evaluate binding versus nonbinding capacity constraints.

The incorporation of bulk density uncertainty for Mineral Resource and Mineral Reserves (MRMR) steps is of great importance for successful mine planning process. In practice, most mining projects u...

38 85 67 M50 М51 The process of creating a geological block model as the basis for a further detailed design and planning of mining operations is a very responsible task. Errors made during this initial process are transferred to all other phases of the mining project. Certainly, one of the most important decisions for the modelling process is the choice of the appropriate size of the blocks that form the model itself. The determination of the optimal block size is not a simple process, because it depends on a large number of affecting factors and criteria. This process can be significantly facilitated by the application of multi-criteria analysis methods, which enable establishment of interdependence between the criteria in order to select the optimal solution. This paper presents the possibilities of applying the Analytical Hierarchical Process (AHP) method for selecting the optimal block size for the needs of the coal deposit modelling process and mine planning, as well as the way in which this method can significantly facilitate problem solving, by looking at it from several aspects. The analysis included six criteria and four potential solutions, and the results themselves indicated the advantages and disadvantages of the applied method.

Block cave mining operations face challenges to meet daily operational production targets. The optimistic long-term and medium-term plans along with uncertainty and the synergistic effect of the me...

In oil sands mining, bitumen and fines contents are used to predict ore processability. However, experimental results show that certain solid fractions known as Organic Rich Solids (ORS) negatively...

This paper presents a chance-constrained integer programming approach based on the linear method to solve the longterm open pit mine production scheduling problem. Specifically, a single stockpile has been addressed for storing excess low-grade material based on the availability of processing capacity and for possible future processing. The proposed scheduling model maximizes the project NPV while respecting a series of physical and economic constraints. Differently from common practice, where deterministic models are used to calculate the average grade for material in the stockpiles, in this work a stochastic approach was performed, starting from the time of planning before the stockpile realization. By performing a probability analysis on two case studies (on iron and gold deposits), it was proven that the stockpile attributes can be treated as normally distributed random variables. Afterwards, the stochastic programming model was formulated in an open pit gold mine in order to determine the optimum amount of ore dispatched from different bench levels in the open pit and at the same time a low-grade stockpile to the mill. The chance-constrained programming was finally applied to obtain the equivalent deterministic solution of the primary model. The obtained results have shown a better feed grade for the processing plant with a higher NPV and probability of grade blending constraint satisfaction, with respect to using the traditional stockpile deterministic model., Rad prikazuje uporabu vjerojatnosnoga cjelobrojnog programiranja, temeljenoga na linearnome algoritmu, za dugoročno rješavanje proizvodnje u rudniku otvorenoga kopa. Obrađeno je jedno odlagalište jalovine sa „siromašnom” koncentracijom rude u cilju aktiviranja toga materijala u budućoj preradbi korisne sirovine. Takav projekt maksimizira trenutačnu vrijednost rudarenja uzimajući u obzir niz fizičkih i ekonomskih varijabli. Posebnost u odnosu na determinističke modele koji se danas uglavnom koriste za izračun granične prosječne vrijednosti koncentracije rude prije odlaganja kao jalovine izražena je stohastikom. Ona je uključila vjerojatnosnu analizu dvaju slučajeva, tj. za ležište željeza i zlata. U obama je dokazano kako se varijable određene na odlagalištu mogu opisati normalnom razdiobom. Stohastički model programiran je za rudnik zlata te je uzeta u obzir optimalna vrijednost rude razvrstane na različitim rudničkim razinama, a prije slanja na obradbu (mljevenje). Optimizirani model zatim je primijenjen za dobivanje usporednoga determinističkog modela. Rezultati su upozorili na to da je konačno rješenje pokazalo znatno bolji odabir granične koncentracije rude koja se mogla poslati na daljnju obradbu. Time je uvećana i ukupna vrijednost rudnika/ležišta.

The development of a multiple level underground mine is a complex task in which geology, engineering, ground control, and unit operations are integrated into a single mine design. The components are inter-dependent and must function cohesively to ensure a profitable underground mining operation. To optimize reserve recovery, mine planning should begin from the lowest level and progress up. This limits any misjudgments or oversights of a given level affecting the underlying levels and ensures the ability to maximize recovery from each level. Mine planning should start with the exploration and characterization of the geologic setting. Once the reserve geology and quality is well understood, then mine planning can begin with respect to the following: (1) orientation of mine works with respect to horizontal stress; (2) access to the reserve; (3) determination of opening widths; (4) selection of back, floor horizons and pillar centers; (5) selection of development and secondary mining heights; (6) appropriate inter-burden thicknesses; and (7) examining the stability of the multiple level mine through numerical modeling. The multiple level mine design process and decisions are presented through a case history example. The theme is that there is one opportunity to “get it right” and many chances to overlook a small aspect within the design that will plague the mine throughout all levels and through the entirety of its operating life. Keywords: Limestone, Mine planning, Geology, Multiple level, Rock mechanics

Molar element ratio analysis of element concentrations consists of four basic tools that provide substantial insight into the lithogeochemistry (and mineralogy) of rocks under examination. These tools consist of: (1) conserved element ratio analysis; (2) Pearce element ratio analysis; (3) general element ratio analysis; and (4) lithogeochemical mineral mode analysis. Conserved element ratio analysis is useful in creating a chemostratigraphic model for the host rocks to mineral deposits, whereas Pearce element ratio analysis and general element ratio analysis are primarily used to identify mineralogical and metasomatic controls on rock compositions and to investigate and quantify the extent of the material transfers that formed the host rocks and mineralization. Lithogeochemical mineral mode analysis converts element concentrations into mineral concentrations using a matrix-based change-of-basis operation, allowing lithogeochemical data to be interpreted in terms of mineral modes. It can be used to provide proper names to rocks, an important activity for an exploration geologist because of the implications that rock names have on genetic processes and mineral deposit models. This paper provides a review of the theoretical foundations of each of these four tools and then illustrates how these techniques have been used in a variety of exploration applications to assist in the search for, evaluation and planning of, and the mining of mineral deposits. Examples include the evaluation of total digestion lithogeochemical datasets from mineral deposits hosted by igneous and sedimentary rocks and formed by hydrothermal and igneous processes. In addition, this paper illustrates a more recent geometallurgical application of these methods, whereby the mineral proportions determined by lithogeochemical mineral mode analysis are used to predict rock properties and obtain the ore body knowledge critical for resource evaluation, mine planning, mining and mine remediation. Thematic collection: This article is part of the Exploration 17 collection available at: https://www.lyellcollection.org/cc/exploration-17

Semi mobile in-pit crushing and conveying systems have different pit shape requirements to traditional truck haulage systems due to the inclusion of a conveyor flight in the pit. As the shape of a ...

Editor’s note: The Geology and Mining series, edited by Dan Wood and Jeffrey Hedenquist, is designed to introduce early-career professionals and students to a variety of topics in mineral exploration, development, and mining, in order to provide insight into the many ways in which geoscientists contribute to the mineral industry. Abstract Mine planning is the process that determines the way in which an ore deposit will be mined over the life of a mining operation. It necessarily draws on everything that planning engineers believe will determine the ultimate success of the proposed mine and uses as its foundation all of the geology-related data on the deposit. It is both a strategic and a tactical process that first considers a longer-term horizon based on strategic considerations, followed by more detailed shorter-term planning processes, in this order; the latter are the result of tactical considerations. This structured process may also be referred to as integrated mine planning, and it is driven by a broader corporate strategy or set of objectives. As such, it is much more than the mining engineering section of the mine development process. It has to include inputs from all related disciplines, by combining all of the measured properties of the deposit with mining-associated parameters. This results in the planning process incorporating a significant number of interrelated parameters. If these parameters are not used diligently and accurately or are not well aligned, or if the underlying data are deficient in either quantity or quality, the project or operation is unlikely to achieve its potential, by virtue of failures in the planning process. Best-practice integrated planning incorporates relevant inputs from all mining-related fields: geology, geotechnical, geochemical, hydrogeological, hydrology, mining operations, minerals processing, marketing of product, waste management, tailings, environmental, social science, mine closure, etc. It includes all interfaces in the business-value driver model, from exploration drill holes to the mine closure plan. The planning process cannot be completed successfully by mining engineers working in isolation from professionals in other key disciplines. Because geology provides the foundation on which the mine plan is built, the quality and accuracy of the geologic data provided to planning teams by exploration geoscientists is crucial.

The main issue in short-term planning optimisation for underground mining is organising the mining process with limited resources in the form of equipment and materials to satisfy production target...

A major trend in mine production planning research is incorporating geological uncertainty in the processes of planning. Many mathematical models and heuristic approaches are proposed to de...

The aim of this work was to study the petrography, geochemistry of the pegmatites, their relationship to the mineralisation in Gitarama and Gatumba areas, and current processes that occurred after the primary emplaced neoproterozoic rare element pegmatites. Previous works on pegmatites were geochemistry and geological maps which are not enough for focused exploration and mine planning. Therefore, geological, petrographic, geochemical studies of neoproterozoic rare element pegmatites of Gatumba and Gitarama areas in relation to their mineralisation were carried out. The samples were analysed for mineral assemblages by petrographic light microscope; major elements by ICP AES; trace and rare earth elements by ICP MS. Petrographic studies revealed the mineral assemblages included quartz, microcline, biotite and major muscovites, which implied that there was the process of muscovitisation occurred after the primary emplacement of pegmatites. The results of geochemical analysis revealed that the silica content (in wt%) ranges from 59.5 - 80.5 with an average of 67.13 (in wt%) for the weathered pegmatite in Gatumba area ,and high percentages of SiO2 (in wt%) range 73.9 - 75.0 with an average of 73.15 (in wt%) for fresh pegmatite in Gitarama area. The pegmatites from Gatumba area were altered and much enriched in Rb (227 - 3460 ppm), Cs (2.59 - 24.7 ppm), Ta (2.6 - 268 ppm), Li (40 - 9224 ppm), W (240 - 10,000 ppm), Nb (13 - 517 ppm), Sn (24 - 8870 ppm). Their enrichment is commonly used as a marker of a magmatic-hydrothermal alteration. Conversely, the pegmatites from Gitarama area showed the low to moderate concentrations in Rb (321 - 337 ppm), Cs (5.47 - 5.62 ppm), Ta (1.3 - 1.6 ppm), Li (~20 ppm), W (5540 - 6410 ppm), Nb (3.9 - 4.3 ppm), Sn (28 - 44 ppm). The variation plot of ratios: Al2O3/(Na2O + K2O) versus Al2O3/(CaO + Na2O + K2O) for the pegmatites from study areas are higher than one (A/NK vs. A/CNK > 1) indicating peraluminous, the other samples of pegmatites indicated metaluminous (A/NK > 1 and A/CNK ΣREE varying between 12.1 - 72.78 ppm and 45 - 54.37 ppm respectively, signifying low to medium form of enrichment. The pegmatite from Gatumba and Gitarama areas showed the K/Rb ratios ranging from 15.74 to 80.26 and from 190.41 to 199.39 respectively. As the pegmatite samples show K/Rb ratios less than 100 are commonly accepted for mineralization, therefore the pegmatites from Gatumba area were found mineralised, conversely to the pegmatite samples from Gitarama area, which were found barren.

Summary Methane gas pockets are intersected during normal mining activities and this causes explosions. Methane gas migrates from deeper sources to mine working environments through faults and dykes. High-resolution 3D reflection seismic method was employed in the western Bushveld Complex to a depth of 1500 m to delineate geological features in subsurface mining environment. Strong seismic reflections were tracked on the seismic cube to create seismic horizons of the platinum-bearing horizons. Preliminary results show faults at various orientations crosscutting the UG2 and Merensky Reef located between 400 – 900 m below surface. Iron-rich ultramafic pegmatoids and potholes were mapped, the former as vertical and chaotic seismic reflection features and the latter as slump structures along the seismic reflections. Spatial correlation between these seismically detected features and methane occurrences influences this research to encourage the implementation of mitigation strategies for future mine planning and development.

Summary Legacy data are defined as previously acquired data that are no longer in use. Their restoration requires substantial time and money, without the promise of yielding rewarding results. These legacy data sets are often accompanied by poorly preserved documentation, outdated coordinates, and are stored on old tech (e.g., tapes or printed versions/hard copies) that make the data hard to use. The new information acquired from the legacy data may profit future mine planning operations by finding new ore deposits, giving a superior estimation of the resources and information that will assist with sitting and sinking future shafts. In this study we present results from the reprocessed legacy seismic data from Witwatersrand goldfields (South Africa). The purpose of the study is to improve the imaging of the gold orebody known as the Ventersdorp Contact Reef (VCR), which is mined at the Kloof Gold Mine. The VCR occurs at an interface between the Ventersdorp Supergroup and Central Rand Group with contrasting densities and seismic velocities, which makes it a good target for the seismic methods.

Production planning decisions in the mining industry are affected by geological, geometallurgical, economic and operational information. However, the traditional approach to address this problem often relies on simplified models that ignore the variability and uncertainty of these parameters. In this paper, two main sources of uncertainty are combined to obtain multiple simulated block models in an iron ore deposit that include the rock type and seven quantitative variables (grades of Fe, SiO2, S, P and K, magnetic ratio and specific gravity). To assess the effect of integrating these two sources of uncertainty in mine planning decision, stochastic and deterministic production scheduling models are applied based on the simulated block models. The results show the capacity of the stochastic mine planning model to identify and minimize risks, obtaining valuable information in ore content or quality at early stages of the project, and improving decision-making with respect to the deterministic production scheduling. Numerically speaking, the stochastic mine planning model improves 6% expected cumulative discounted cash flow and generates 16% more iron ore than deterministic model.

Since the Gol-Gohar iron ore mine (GGIOM), which is located in southeastern Iran, is currently one of the biggest iron mines in this region, increasing the accuracy of its mineral resources model has become a challenge for geologists, metallurgists and mining engineers. Given that an accurate classification of the mining blocks into ore or waste is highly significant in strategic mine planning, three approaches for simulating the iron grades were compared against the true grades obtained from production data. The comparison was done by calculating the ratio between the total number of blocks correctly classified as ore and waste and the total number of misclassified blocks, and it was conducted for each approach in three mined benches at the GGIOM. The results reveal that the grade simulation that ignores the geological boundaries and the grade simulation based on a deterministic geological interpretation are much less accurate than the hierarchical approach, which consists of simulating both the geological boundaries and the grades.

Chalk occurs in northern Europe from the southern UK to eastwards deep into Russia. It is exploited as an industrial mineral for a large variety of uses. From the examples of three different chalk mining operations, it is shown that although geologically and geochemically quite similar, all three deposits have very different physical and geomechanical properties which in turn have impacts on slope designs as well as mining method, mine planning and equipment selection.

Kalan is one of the focus areas for uranium exploration in West Borneo that conducted by BATAN. Situated in the central part of Kalan, previous works in Rabau Hulu Sector consisted of surface geology and radiometric anomaly mapping, trenching, drilling, logging, and conventional uranium resource estimation. Nevertheless, the complete resource estimation of the previous work was still using 2D modeling, and the latest one using 3D modeling is a method-application case study in one orebody. To increase the confidence level and completing the uranium resource estimation of all orebodies in this sector, a geostatistical estimation with 3D orebody modeling using SURPAC mine planning software was conducted in this paper. Gamma-ray log data from 32 drill holes were collected and then interpreted to obtain uranium grade-thickness data. Based on the correlation of grade-thickness data according to surface orebody orientation, the orebody 3D modeling was done. It resulted in 26 orebodies with one control system of lithology as the mineralization only taken place in the quartzite unit. This 3D model then used as a constraint for block model with 4x4x2 m block size and 0.25x0.25x0.125 m minimum block size. Block model calculation was performed using ordinary kriging which generated the kriging efficiency attribute for the determination of the resource category. Within 25 meters searching radius, the calculation resulted in 408, 480 tons of ore, while total uranium resource was 268 tons of uranium with 677 ppm average grade. There were 214 tons of uranium (79%) categorized as measured while the other 54 tons of uranium (21%) categorized as indicated.

The BHP Olympic Dam underground mine site has experienced ongoing issues with overbreak within its stopes in the recently-developed Southern Mining Area. The rock mass is poorly characterised and there are limited data on key structures influencing the ultimate shape of stopes and the extent of overbreak. The introduction of the Emesent Hovermap mobile drone LiDAR system has provided more extensive, accurate scan coverage of existing stopes, some which were previously inaccessible via earlier scanning methods. This new approach provides a much higher resolution scan than does the industry standard Cavity Monitoring System. With these data, a new methodology of digitally geo-mapping exposed structures within the stopes has been developed to create a new dataset. This is now used for further mine planning through comparing, validating, and appending to modelled geological structural features. This paper discusses the process of acquiring and preparing drone-based LiDAR data for geomechanics and explores the spatial and structural relationship between drone data and window mapping for implementation into Olympic Dam's future stope designs. The back-analysis of stope failures through the LiDAR scan structural mapping has provided a great deal of insight into structural characterisation of underground areas and can assist in planning future stopes. It has not only provided more detailed information on the previously identified large persistent structures but has also identified large multi-stope spanning structures which were previously unrecognised. Evidence of broader zones of weakness, more extensive than previously appreciated, were also uncovered through small-scale structural persistence through mine areas.

Based on the differentiation of coal ash content into constituents, the procedure is developed for estimating overall (technological and natural) dilution. The accumulated data base on the Elgin coal deposit (South Yakutia) is described. This data base was used to model coal seams for studying variability of their parameters and properties. The estimated ash contents due to mining operations and connected with the discriminated natural groups of mineral admixtures are presented. Higher variability of the overall ash content and its components across the area and in section of coal seams is shown. The percentage of various thickness steaks inside coal seams in the structure of ash content may reach 14–27% and more. Coal mines insufficiently account for this fact, which leads to incomplete utilization of geological potential of complex-structure deposits. It is emphasized that the resource-saving ash content control should not only be focused on processing efficiency. Based on additional appraisal of mineral reserves, it is possible to gain new capabilities of control at the stages of mine planning and design, actual mining and coal pretreatment.

Stope layout optimisation finds a technically producible orebody portion that maximises the profit of the mining operation based on the stoping method used. A three-stage stochastic optimisation mo...

The coals of the Brazil and the lower part of the Staunton Formations (Atokan and early Desmoinesian, Pennsylvanian) in Indiana (Illinois Basin) are typically thin and discontinuous. As a result, both researchers and the industry have experienced problems with coal bed identification and correlation. The discrepancies in coal nomenclature and frequent miscorrelations affect coal exploration, mine planning, and communication between mines and customers. Our previous study, based on exploration boreholes, mine-scale observations, and coal quality and petrographic data from Daviess, Greene, and Clay Counties, Indiana, suggested that the coal mapped as the Upper Block Coal Member of Clay County might be the same seam as the Lower Block Coal Member of Daviess County. This study is an extension of the previous research conducted farther south to Pike, Warrick, and Spencer Counties, Indiana. In the southern part of Indiana, correlation of these late Atokan and early Desmoinesian coal beds is even more difficult because of the absence of well-defined marker horizons and limited mining and subsurface well data. Although palynological and coal petrography data generally correspond, these data alone cannot resolve the correlation of the coal beds in this southern region with the coals of Clay or Greene Counties, and they must be supplemented with the analysis of associated limestones. The ability to accurately identify the Perth Limestone Member, which occurs close to the Buffaloville Coal Member of the Brazil Formation, and the Holland Limestone Member, which occurs higher up in the Staunton Formation, will help to distinguish between Brazil and Staunton Formation coals.

Kevitsa is a disseminated Ni-Cu-PGE (platinum group elements) ore body in northern Finland, hosted by an extremely high-velocity ([Formula: see text]) ultramafic intrusion. It is currently being mined at a depth of approximately 100 m with open-pit mining. The estimated mine life is 20 years, with the final pit reaching a depth of 500–600 m. Based on a series of 2D seismic surveys and given the expected mine life, a high-resolution 3D seismic survey was justified and conducted in the winter of 2010. We evaluate earlier 3D reflection data processing results and complement that by the results of 3D first-arrival traveltime tomography. The combined results provide insights on the nature of some of the reflectors within the intrusion. In particular, a major discontinuity, a weakness zone, is delineated in the tomography results on the northern side of the planned pit. Supported by the reflection data, we estimate the discontinuity, likely a thrust sheet, to extend down approximately 600 m and laterally 1000 m. The weakness zone terminates prominent internal reflectivity of the Kevitsa intrusion, and it is associated with the extent of the economic mineralization. Together with other weakness zones, a couple of which are also revealed by the tomography study, the discontinuity forms a major wedge block that influences the mine bench stability on the northern side of the open pit and likely will cause more issues during the extraction of the ore in this part of the mine. We argue that 3D seismic data should routinely be acquired prior to commencement of mining activities to maximize exploration efficiency at depth and also to optimize mining as it continues toward depth. Three-dimensional seismic data over mineral exploration areas are valuable and can be revisited for different purposes but are difficult to impossible to acquire after mining has commenced.

This contribution presents an updated descriptive scheme for magmaclasts in kimberlite, resulting from over 40 combined years of mapping, logging, and petrographic studies by the authors of hundreds of kimberlites and related rocks globally. Systematic description of the essential characteristics of magmaclasts enables their identification, classification and interpretation. Magmaclasts are fluidal-shaped bodies of kimberlite magma (now solidified) formed by any process of magma disruption prior to solidification. The key characteristics used to discriminate the two main varieties, melt segregations and melt-bearing pyroclasts, are explained and illustrated, as well as the features of melt-bearing pyroclasts in the two main classes of pyroclastic kimberlite. Accurate classification of magmaclasts in coherent and volcaniclastic kimberlites is fundamental for the development of valid geological models in support of exploration, evaluation and mine planning. Magmaclasts are used to determine parental magma type, the textural-genetic classification of the infills of kimberlite bodies, the presence of different eruptive phases (and mixing between them), and the emplacement history of a kimberlite. They can also provide insight on potential modification of the inherent diamond distribution of a kimberlite.

We tested the applicability of a newly developed broadband (0–800 Hz) digital-based seismic landstreamer for open-pit mine planning in the apatite-bearing Siilinjärvi mine in central Finland. Four seismic profiles, in total approximately 2.5 km long (2–4 m source and landstreamer receiver spacing), two inside the pit and two on its margins, were acquired in combination with wireless recorders connected to 10 Hz geophones and fixed at every 10 m spacing along the seismic profiles while the streamer data were being acquired. Downhole logging and laboratory physical property measurements on core and rock samples were carried out to not only support the seismic interpretations but also to provide information about the possible geophysical signature of these unique types of deposits. In spite of a highly noisy mining environment, seismic data of high quality were acquired; however, reflection processing and interpretations were challenged by the geologic complexities of several generations of basic and carbonatite dikes. To complement the reflection data imaging and to account for the steep elevation changes and crookedness of some of the seismic profiles, 3D first-arrival traveltime tomography and 3D swath reflection imaging were also carried out. Clear refracted arrivals from the open-pit profiles suggest the possibility of low-velocity zones associated with either blasting or several shear zones intersecting the seismic profiles. In terms of reflectivity, reflections have a different appearance from short and flat to longer and steep ones. The downhole- and borehole logging data suggest that some of these reflections are associated with diabase dikes and some are likely from zones of weaknesses in the alkaline-carbonatite complex. We determine the potential of using seismic streamers for cost- and time-effective open-pit mine planning and encourage further testing in simpler geologic settings to be established.

The traditional mine planning framework employs a flawed approach in the design of ultimate pit limits and phases. Conventional methods arbitrarily confine the mine’s extraction schedule during the initial stages, detracting from its optimality before it is created. This work aims to provide a method by which a mine’s phase design is created from an optimal extraction schedule. The schedule-based approach to phase design yields implementable mining phases that mimic the initial raw optimal schedule from which it is based. An attempt to minimise the trade-off between mineability and value is inherent to the approach.

The objective of this study is to integrate the admissible factor of safety (FoS) into the mine planning. The analysis showed, as expected, that a lower net present value (NPV) is obtained with the increase in the admissible FoS. Most importantly, it demonstrated that the FoS of the slopes of the adjacent phases, which are not part of the final pit, are considerably greater than the admissible FoS. Therefore, the NPV of an open pit mine project can be increased by steepening the slopes of adjacent phases that are not part of the final pit walls.

Complex structure of the subsurface in hard rock environment often complicates traditional processing and interpretation of seismic datasets based on the analysis of reflected waves. Full-waveform inversion (FWI), in turn, utilizes the whole wavefield, including the transmitted waves and reflections, to build the models of physical properties (such as P wave velocity and density), which is one of its main advantages over traditional methods of seismic imaging. We conduct a feasibility study of 2D full-waveform inversion (FWI) applied to vertical seismic profile (VSP) synthetic data computed in a model that is based on a real hard-rock survey site for the purpose of identification of heterogeneities. Using this complex model of the subsurface that contains steep interfaces, high seismic wave velocities and densities, we generate a synthetic VSP dataset with a finite-difference code. Multi-offset VSP geometry is considered due to the abundance of transmitted waves. We then apply FWI to this dataset. We use finite-difference modelling for the forward problem in FWI, optimization is conducted using the limited-memory BFGS method. FWI is applied in a multiscale manner, from 10 Hz to 190 Hz. Inversion results suggest that FWI of VSP data is a suitable tool for building the models of physical properties of the subsurface that are crucial for mineral exploration and mine planning.

Long-term open-pit mine planning is a critical stage of a mining project that seeks to establish the best strategy for extracting mineral resources, based on the assumption of several economic, geological and operational parameters. Conventionally, during this process it is common to use deterministic resource models to estimate in situ ore grades and to assume average values for geometallurgical variables. These assumptions cause risks that may negatively impact on the planned production and finally on the project value. This paper addresses the long-term planning of an open-pit mine considering (i) the incorporation of geometallurgical models given by equiprobable scenarios that allow for the assessing of the spatial variability and the uncertainty of the mineral deposit, and (ii) the use of stochastic integer programming model for risk analysis in direct block scheduling, considering the scenarios simultaneously. The methodology comprises two stages: pit optimization to generate initial ultimate pit limit per scenario and then to define a single ultimate pit based on reliability, and stochastic life-of-mine production scheduling to define block extraction sequences within the reliability ultimate pit to maximize the expected discounted value and minimize the total cost of production objective deviations. To evaluate the effect of the geometallurgical information, both stages consider different optimization strategies that depend on the economic model to be used and the type of processing constraints established in the scheduling. The results show that geometallurgical data with their associated uncertainties can change the decisions regarding pit limits and production schedule and, consequently, to impact the financial outcomes.

Stochastic mine planning algorithms have been extended to better represent ore selection decisions. Under geological uncertainty, existing algorithms generate plans that may violate the mineral processing capacity; under such geological scenarios, the excess ore undergoes a recourse action which is not as profitable as regular processing, hence decreasing the net present value. This decrease has previously been represented as a penalty on excess ore, which may not accurately represent actual operations. The new framework considers the most typical recourse: increasing the cut-off grade into the mineral process. This approach is demonstrated by adapting the VND algorithm of Lamghari et al.

The authors provide their assessment of current challenges in strategic mine planning and some approaches for addressing them. Challenges covered are quantification of downstream processes and their integration into orebody models; spatial characterisation of geometallurgical variables and their integration into block models, scheduling and mine optimisation; spatial characterisation of new variables for new types of mining; flexibility in planning and design to manage risk and minimise its impact; IT infrastructure for rapid on-line data collection and processing. Most of these challenges require new types of data, variables, modelling and estimation methods. Foremost among new variable types are geometallurgical and dynamic rock mass characterisation variables. New types of data and data collection include rapid generation of very large amounts of on-line sensor data and the consequent need for rapid processing and modelling of these data. The paper includes examples of models and outputs to illustrate ...

A mining complex may be comprised of multiple components, including open-pit and underground operations. Traditional approaches in mine planning do not account for the various components simultaneously leading to under-value solutions. Over the last decade, some methods have been developed to incorporate multiple components of the mining value chain during optimisation. Even though these new methods incorporate more decisions and flexibility to the optimisation of a mining complex, they may either ignore uncertainties associated with the mining project or consider decisions taken before optimisation. This paper presents a method that optimises mining complexes comprised of multiple open-pits, underground operations and processing destinations. Mining, blending, processing and transportation decision variables are simultaneously optimised while accounting for geological uncertainty. The method uses a simulated annealing algorithm at different decision levels in order to generate a stochastic-based extracti...