Search Documents

By Jesús Cruces

La fragmentación de rocas es unos de los procesos más importantes dentro del proceso productivo global Mina- Concentradora -en tanto genera rentabilidad y mayor tonelaje tratado durante la etapa de trituración y molienda. En esta perspectiva, el presente texto señala no solo el incremento de la producción en la Concentradora (toneladas/hora que tratan las trituradoras y molinos), sino también de las palas, mejorando el volumen cargado. Para ello, se optimiza el llenado de las tolvas de los volquetes y los vagones con material homogéneo y menor espacio intersticial desperdiciado.

Sep 12, 2011

By Raymond Rivera

El presente texto describe la evaluación desarrollada por INGEMMET donde se analiza el potencial de los depósitos minerales en el Batolito Andahuaylas, Yauri, así como el potencial de algunas zonas que presenten características geoeconómicas importantes, utilizando herramientas geológicas como geocronología, isótopos radiogénicos, geoquímica de rocas y sedimentos, petromineralogía y geología estructural.

Sep 12, 2011

By Martín E. Mendoza

En 2010 se identificó un peligro potencial en la pared Norte del Tajo Chaquicocha, donde existía fallas pre-existentes, catch bench reducidos (subestándar) y bloques colgados que presuponían condiciones de mala voladura de control. Por ello, se planteó la modificación del diseño Final del Tajo Chaquicocha, ya que la continuidad de estos malos resultados arriesgaba el minado de los Bancos inferiores. En ese sentido, el objetivo del presente texto estriba en lograr voladuras masivas, sin afectar la estabilidad de las paredes del Tajo Chaquicocha, así como tener beneficios económicos en la reducción de tiempo de minado por cada banco, y en la productividad (Dig Rate) de los equipos de carguío.

Sep 12, 2011

By . Jaime G Tapia Aguirre

La Unidad Minera Rosaura del Grupo Glencore fue considerada la mina subterránea más segura del país durante los años 2005, 2006 y 2007. Sin embargo, cuando el Grupo Glencore adquirió la concesión de Rosaura, el panorama minero era de una mina marginal, de bajas leyes. Por esta razón, el único metodo a ejecutar para hacer de Rosaura una mina rentable era el de utilizar un método masivo. Em ese semtido, el presente texto señala la operación de mina cone el análisis y conocimiento de causa raíz en la prevención de caída de roca.

Sep 12, 2011

By José M. Chiroque

Ante la necesidad de ventilar las labores de la profundización en la rampa Rick 3, se genera el proyecto de ventilación denominado Raise Borer RB12 como un circuito de extracción de aire viciado. Sin embargo, por las características geológicas de las rocas encajonantes de esta chimenea y por la intemperización de las mismas por cercanía a superficie, se identificó desprendimientos de roca de las paredes de este RB, comprometiendo su estabilidad con posibilidades de atrancamiento y taponeo con carga. En consecuencia, se perjudica la ventilación de la profundización y los costos de inversión por la necesidad de construcción de una nueva chimenea. Por ello, el objetivo del presente trabajo busca garantizar la vida útil de la chimenea a través del diseño y construcción de un sistema mecánico de izaje y descenso para la chimenea RB 12A, donde se utiliza un winche, cables y una jaula, considerando todas las medidas de seguridad. Luego, fue lanzado el shotcrete y colocación de ductos metálicos en la zona ensanchada, cumpliendo con el objetivo de la recuperación y garantizando la vida útil de esta chimenea.

Sep 12, 2011

By Marco Taipe

Uno de los mayores costos del proceso minero es el de perforación, en tanto emplea aire comprimido. Por tal motivo, la industria minera busca diferentes alternativas para reducir los costos del aire comprimido o eventualmente a través del uso del sistema electro-neumático. Este sistema es de fácil instalación y mantenimiento puesto que se basa en electricidad y agua, reduciendo costos y a su vez mejorando las condiciones de trabajo a través de la versatilidad del presente sistema.

Sep 12, 2011

By Víctor Carlotto

Los estudios geológicos definen los nuevos dominios geotectónicos del territorio peruano -en tanto esta división es la base para elaborar los nuevos mapas metalogenéticos del Perú. En este sentido, el presente texto describe los mapas de dominios geotécnicos y metalogenéticos peruanos como herramientas aplicables a la prospección y exploración de los recursos minerales, como en la planificación del territorio. El mapa es presentado desde la perspectiva de la geología regional y muestra 25 franjas metalogenéticas, basadas en los 13 dominios geotectónicos previamente evidenciados.

Sep 12, 2011

By Mafalda Arias

The role of our industry is essential to future societal needs and to set the foundation for a better world, it?s important to built trust and relationships inside your global team, within communities and together with stakeholders. The objective of this paper is to raise awareness of the importance of including “culture” as one of the four pillars of sustainability and to highlight the disjointed nature of the existing concept of sustainability and the goal of that concept. In other words, the conflicting propositions between the western beliefs that set the foundation of the sustainability concept and the eastern beliefs that aims to have sustainability as an end result. The incorporation of “culture” aims to find a balance, which unites these opposite perspectives to result in a more harmonious solution for society.

Sep 12, 2011

By A Stradling

For a geometallurgical program to be successful, linkage must be made between the geologists and geostaticians who understand and model the orebody, the metallurgists who determine the value that can be extracted from the different geometallurgical units, and the mine planners who develop and optimise the plan to extract maximum economic value from the resource. One of the primary purposes of geometallurgical models is in the determination of the economic cut-off between ore and waste. Recognition of the level of confidence required in the estimation of grade, throughput and recovery is critical to the planning of a successful geometallurgical program. It also helps clarify the scope of work needed to mitigate risk at each stage in the development of a new mine projectThis presentation provides some of the author’s experience with development and application of geometallurgical models for existing base metal operations. It discusses how geological units defined by lithology, structure, alteration etc, can be translated into geometallurgical ore types defined by mineralogy, ore hardness, and flotation behaviour. Examples of how these characteristics have been used to estimate key economic parameters such as mill throughput and flotation recovery at two brown-field operations are provided. The first example relates to the modelling of metallurgical performance at Teck’s Red Dog zinc-lead mine in Alaska. Prior to 2000, zinc, lead and silver recoveries from a block of ore at Red Dog were either assumed constant, or were varied according to simplistic models. Throughput was not thought to vary substantially between blocks, so an average value was used for each blended stockpile. It is quite possible that some ore-value blocks were classified as waste, and some waste-value blocks treated as ore, as a result of poor understanding of the true economic cut off across the wide range of ore types observed at Red Dog. After an extensive flotation test program, the first assay-based zinc recovery model was developed for the Main pit reserve in 2003.**This is an abstract only. No paper was prepared for this abstract**

Sep 5, 2011

By M Oyarzún

Direct relationships between rock texture and BWi (grindability index) have been established based on geological and metallurgical information supported by optical microscopy observations, gathered from 731 samples.Each recognised rock texture is observed to be related to a certain BWi range and, this texture is also characteristic of distinct lithological subunits (recognisable at mapping scale). Therefore, this relationship may provide an important tool for early milling in situ estimation.Since each textural type is a response to rock formation conditions, the causality of the relationship between BWi and texture is based on such conditions and, particularly, on the interfacial free energy among its components.According to the abovementioned textural features, the greater the free interfacial energy between mineral components, the greater the necessary energy required to break its grain boundaries and, consequently, the greater the necessary energy required for milling.If the textural evidence indicates that the rock was able to adjust the shape and/or size of its components – in a natural tendency of all systems to minimise energy– then the necessary energy required to break its grain boundaries will be lower.

Sep 5, 2011

By D Lawie

Prior to resource modelling, sample scale data is normally grouped into spatial domains that reflect zones of homogenous properties. These domains are usually based on a combination of grade and other variables that reflect, for example, geology and alteration, or variables known to correlate with properties of the samples that affect downstream processing. Domaining and wire-framing sample scale data is a time intensive task and it is difficult to track more than a few variables simultaneously while establishing domain boundaries. This is especially the case in operations with complex data, for example, a combination of multi-element assaying of total element concentrations, and/or phase specific assaying such as sulfide sulfur, carbonate carbon, cyanide available gold, and/or downhole geophysical measurements. To minimise unintentionally grouping samples of contrasting properties within the same domain, unsupervised statistical methods are available that can automatically identify samples atypical of the domain, both as univariate tests, and as tests that take correlation within the domain into account. Unsupervised methods in this context means methods of identifying atypical samples that require just the selection of the domain and input variables. Thresholds are derived robustly from the data itself, and the results are therefore repeatable and operator independent. Atypical samples may be thought of as outliers, ie, samples that are separated from the ‘majority’ of the data. If these atypical samples are themselves spatially associated, they may be allocated to an alternative existing domain or allocated to a new domain. Care should always be taken to ensure that identified outliers are due to meaningful causes and not due to data coding and storage errors, although the identification of the latter is still valuable. *This is an abstract only. No paper was prepared for this abstract.*

Sep 5, 2011

By L Keeney

Geometallurgy is not a mechanism designed to replace current geological and metallurgical deposit characterisation but an added component required to understand orebody variability. Current geological characterisation approaches focus on understanding deposit genesis aimed at identifying new mineralised regions and metallurgical characterisation determines parameters required for engineering design of processing plants. Geometallurgical integration has the task of drawing on aspects of each stream to enable spatial mapping of performance indices across a deposit. It is a complimentary activity to current practice and adds a new dimension to orebody knowledge. Although the notion of conducting an integrated geological and metallurgical analysis is not a new concept, limited publications exist in the field proposing integrated methods, with several technical issues existing in current geometallurgical integration approaches. An iterative method drawing on existing geological and metallurgical characterisation and new measurement tools and inputs is proposed. The integrated method comprises of discrete components dynamically linked together through iterative feedback loops with each component having a specific purpose achieved by applying a range of data acquisition technologies and statistical tests. The key outcomes of the method are:overcoming the lack of optimised geometallurgical domains relevant to processing performance,development of a rigorous approach to identifying parameters controlling processability,improved protocols for relevant metallurgical test data and sample selection, andability to generate greater data support to enable rigorous geostatistical modelling of geometallurgical attributes. This paper outlines the integrated mapping and modelling method developed and draws on multiple data acquisition technologies applied within the AMIRA P843 GeMIII Project.

Sep 5, 2011

By G Turner-Saad

An improvement to cut-off grade optimisation theory based on geometallurgy has been completed. The improvement fundamentally consisted of taking into account mineralogical and textural characteristics instead of grades. These characteristics are related to the spatial variability of mineral abundance, association, particle size and liberation properties. Additionally, the improve- ment considered the spatial variability of mineral processing liberation and selectivity properties associated with mineralogy and texture. The enhanced optimisation enables estimation of the economic value of mining operations based on an optimum cut-off policy attributed to liberated and selected ore minerals.The enhanced optimisation was developed as an essential component of a joint cut-and-fill mining and mineral processing methodology based on mixed integer mathematical programming. The formulation considers static and dynamic modifying factors that vary over the projected life of mining. The objective function of the mathematical formulation consists of maximising the realistic expected economic value of concentrates or products of liberated and selected ore minerals, whilst minimises liberated and selected gangue minerals. The optimal solution is obtained when the objective function is subject to geological, mining, processing, marketing, smelting, refining, environmental and financial constraints. The methodology accesses geometallurgical multivariate resource models, which integrate the spatial variability of mineralogical and textural characteristics and mineral processing liberation and selectivity properties.The geometallurgical process concurrently optimises stope geometries, ore reserves, mining sequences, and mining and mineral processing production based on the enhanced cut-off of liberated and selected ore minerals. In addition, the process considers additive and non-additive transfer functions associated to mutually exclusive geometallurgical spatial domains. The transfer functions also take into consideration the blending of mineralogical and textural characteristics with mineral processing liberation and selectivity properties.This contribution presents an example of cut-off grade optimisation via mineralogical and textural characteristic, and liberation and selectivity processing parameter optimisation for a spatially variable orebody.

Sep 5, 2011

By P Kittler

In the spectrum of mining-related disciplines, geometallurgy sits between resource geology and metallurgical engineering. Unlike its neighbours, it is a relatively young discipline and its concepts, procedures and techniques are still evolving. Relevant geometallurgical issues differ from one deposit to the next so there is no single template that can be used in all situations, meaning that geometallurgy programs are nearly always customised and tailored to the deposit and the situation.Over time, a number of key mistakes are seen to emerge regularly. The eventual impact of these mistakes can vary from suboptimal performance of mine and plant to complete failure of the operation. For instance, poor characterisation of ore lithologies and their spatial distribution can have negative impacts on processing plant throughput. However, when combined with failure to identify critical blending constraints it can result in a totally inoperable plant.A number of common mistakes committed during geometallurgical programs are discussed and some preferred alternative approaches are suggested

Sep 5, 2011

By J E. Everett

An essential requirement of product quality control in the mining industry is to be able to reliably predict key quality properties of finished product from the data available before the extraction of the ore. From a production viewpoint, the unit of data collection is generally the input and output data set for each shift of crusher production, but could be any period where mine precrusher data can be reliably matched with product data.This paper demonstrates that linear regression models can be used to predict crush grades from blast grades, even where the crush material is blended from multiple sources or pits for each of which differing regression models might apply. The advantage of using increasingly complex regressions models to match the available data to give increasingly more powerful models is examined. The best model for any application will be a balance between required predictability, available data and the business’ tolerance for complex models.The regression modelling approach has several advantages over the more classic method of run-of-mine (ROM) crusher trials, which will be discussed.The models can use any predictor variable such as grade, geotype and in situ density provided the preextraction data set can be reliably matched with post-crusher data and is significant as a predictor. The models have been used extensively in the generation of the daily crusher plan with the aim of maintaining finished product grade. This approach has also been used associated with exploration drilling and long-term planning.It is acknowledged that there are inherent problems in fitting lump and fines grade to a linear model. However, these problems are minor when they are used for interpolation within the window spanned by the shift blend records used to produce the model. This paper discusses some of the issues limiting linear regression models in this application, and suggests methods enabling consistent models to be formulated

Sep 5, 2011

By S Walters

The emerging discipline of ‘geometallurgy’ is not new but is becoming increasingly recognised as a discrete and high-value activity. Geometallurgy involves a quantified and spatially constrained approach to ore characterisation in terms of relationships to critical processing performance behaviours. A key outcome is enhanced economic optimisation of mining and improved risk management tools.Industry recognition of the need for large-scale, integrated research to support this emerging area resulted in commencement of a major ongoing initiative in mid-2005. The AMIRA International P843 ‘GeMIII’ project (Geometallurgical Mapping and Mine Modelling) is a cross-discipline collaboration involving a number of world-class research organisations supported by over 20 industry sponsors.The project is delivering integrated tools and methods which link intrinsic rock characteristics to prediction of mineral processing performance. These indices must be capable of spatial distribution in 3D resource models and incorporation into mine planning and optimisation. A key aspect is provision of new cost-effective tools and methods which can provide the large numbers of measured and estimated data points required to undertake effective modelling and spatial distribution. The integrated methodology and enabling technologies being developed through the ongoing AMIRA GeMIII project are outlined, together with implications for supporting industry best practice.

Sep 5, 2011

By J Jackson

The term geometallurgy (or geometallurgical) first appeared in the literature some 40 years ago and has a wide range of definitions and perspectives which increases the barriers of communication between practitioners and across functional groups and management levels within organisations. However the consistent theme running through the diversity of definitions and perspectives is the requirement for close collaboration between the relevant disciplines. This concept of geometallurgy arguably goes back to the earliest days of the exploitation of mineral deposits, through the mid-1500s to the beginning of the 20th century.This holistic and integrated view was diminished during the 20th century due to a number of factors which included the commencement and continuing upward trend of large-scale mining and the expansion in production, the rise of scientific and classical management theories and methodologies, increase in specialisation and the development of traditional project planning. The re-emergence of geometallurgy in the late 20th century required the relevant functional units and disciplines to collaborate as a team. This necessitates a common understanding that the geometallurgical program’s goals must be obtained, which requires clear and consistent communication, particularly with the modern trend of virtual teams.A multi-dimensional construct is proposed to assist in providing a consistent approach in the communication of the context and purpose of both general and specific geometallurgical programs, thus simplifying communication. This geometallurgical construct consists of the dimensions of process span, response knowledge, variability knowledge, spatial knowledge, application and project phase in relation to extraction process(es) applied to geological materials from a mineral deposit. These dimensions are then linked to the phase of mineral project development in which the geometallurgical program is being applied, which ranges from advanced exploration through to operational execution. This paper outlines the multi-dimensional construct with examples of how the context, purpose and scope of geometallurgical programs can be clearly delineated and communicated.

Sep 5, 2011

By R Berry

This paper looks at two ways to estimate the bulk mineralogy of the rocks for assay intervals. The aim is to find an efficient indicator of the most common minerals in the rock. Phase (modal) analysis has traditionally been done using visual methods such as point counting and image analysis. A modern version of this process is the X-ray point counting routine using the SEM-EDS based software. These methods are too slow and expensive for routine analysis of bulk sample mineralogy at the normal assay spacing.Two sources of data were considered that provide information that can be used to determine the mineral abundance in assay samples. The most widely applied method is (semi-) quantitative X-ray diffraction (QXRD). The QXRD method is most applicable to major minerals and has limited application to minerals at low abundance. The nominal detection limit is 0.5 per cent. Values below five per cent have large errors. A second, less common, method is calculation of mineralogy from chemical assay data. Conversion of chemical analyses to mineralogical analyses depends on the unique chemical composition of each mineral. Elements only found in one mineral are easily accounted for, but many compositions are ambiguous. Deciding on the actual mineralogy is not simple. Recalculation of mineral mode from chemical analyses is more accurate than QXRD when the correct minerals, and mineral compositions, are known.Where only a few QXRD analyses are available they can be used to setup a protocol for calculation of mineralogy from assay data. Linear programming works well in this environment. The best results are obtained when both H2O and CO2 are directly measured. Loss-on-ignition (LOI) should be included if these are not available.Where both QXRD and chemical analysis are available for all samples, the best results are obtained using the least squared method to merge the data sets assuming QXRD has much higher analytical errors than chemical assays. The combined method provides more robust results because the high abundance minerals are controlled by the QXRD measurements while the chemical assays improve the precision for low abundance minerals

Sep 5, 2011

By A R. Bye

The mining industry is facing some key challenges that provide a compelling case for geometallurgy initiatives. Over the last 30 years, the average grade of Australian orebodies being mined has halved while the waste removed to access the minerals has more than doubled. In the last eight years, the industry’s energy consumption has increased 70 per cent while multi-factored productivity has fallen 24 per cent. The paper documents a broad range of industry case studies which demonstrate strategies for gaining value from geometallurgy.The mining industry constantly faces the key questions of how significant ore variability is on mine valuation and how would knowledge of the variability change the mining schedule, mine to mill design and operation. Using case studies the paper describes the methods used for incorporating mineral extraction attributes into orebody models and their technical integration into daily operation as well as mine planning optimisation. While pit optimisation from a fully attributed geometallurgical model highlights areas of opportunity and risk it is shown that during the scheduling phase of mine planning that significant value can be added. The benefits from these projects included reducing geotechnical and environmental risk, improving mine to mill performance, option analysis and quantified cash flow risk. There is growing acceptance within the minerals industry that ‘realistically assumed modifying factors’ defined by a competent person/s are not sufficient to mitigate the risk of funding mining ventures. Geometallurgy is moving away from factored ore reserves to data-rich block models providing reliable information for mining, metallurgical and environmental considerations.

Sep 5, 2011

By R Baumgartner

The Canahuire deposit is a recently discovered Au-Cu-Ag epithermal deposit in Southern Peru. A geometallurgy program is a key study element of the project Feasibility study. Metallurgical, mineralogical, and comminution studies have been completed over a suite of samples, spatially distributed among the various geological/ore domains. The early stage of Canahuire presents challenges as there is a lack of metallurgical information to guide geometallurgical sampling, in contrast with an established deposit at a more advanced stage of development or mining. Nevertheless, the available information will assist in the development of geometallurgical domains for Canahuire in order to ensure that future metallurgical, mineralogical, and comminution test work is representative of the deposit variability. This supplementary knowledge will be able to predict important metallurgical parameters which will be incorporated into a geometallurgical model to spatial predict material types, metallurgical recovery and through put. The information obtained will be a valuable addition to the future mine plan, influencing process design, engineering design, plant operation, operating and capital costs, and ultimately will reduce project development risk.

Sep 5, 2011