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By H Masoumi, I Canbulat, Y Zhao, J Oh, H Lin

Borehole breakout is a drilling induced phenomenon caused by overstress of rock around the borehole. Its depth usually aligns with the minimum horizontal principal stress direction. For this reason, it has been used to determine stress orientations and a series of researchers also argued its dimensions can be indicative of stress magnitudes. If the stress dependencies of breakout geometries are well understood, it is possible to estimate stress magnitudes based on these data. This paper investigates the influences of critical parameters on breakout dimensions, including absolute stress magnitudes, stress ratios and borehole diameter. Several experiments have been conducted on cubic (120 x 120 x 120 mm3) sandstone samples with pre-drilled holes (22 mm and 30 mm) under true tri-axial loading conditions using UNSW self-designed equipment. Experimental results confirm the increasing maximum horizontal principal stress magnitudes result in larger angular span and longer breakout depth at constant minimum horizontal and vertical principal stresses. There is also a considerable discrepancy observed between experimental results and the analytical model. Findings of this study imply a potential on the estimation of stress magnitudes using borehole breakout. CITATION:Lin, H, Oh, J, Canbulat, I, Masoumi, H and Zhao, Y, 2018. Experimental investigation on borehole beakout and its implication on stress magnitudes, in Proceedings The Fourth Australasian Ground Control in Mining Conference (AusRock), pp 266–273 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 30, 2018

The application of cheap robust microprocessor based units to achieve monitoring and control in an underground mining environment is described. The functional layout of the programmable controller and the methods of multiplexing and processing information from local and remote sources are examined as are features for refrigeration plant control.High noise immunity communication to a remote micro computer uses existing telephone lines and enables display and print of essential data. The development of this system then leads to applications in monitoring compressed air, ore transport and underground fires.In conclusion, the problems of data presentation to different levels of management and the future philosophy of a central multi-reporting system are discussed.

Jan 1, 1985

By Lo YC, Pate WT

In recent years there has been a great deal of interest in ways to optimise the performance of mineral processing plants. This paper describes a methodology developed for optimisation of autogenous and semiautogenous mills. The methodology involves plant sampling, batch testing, modelling, computer simulation, control strategy evaluation and implementation. The models have been tested in plant operations to verify the research findings and predictions. Two example applications of this approach to plant optimisation are presented. Benefits reported in these two examples are in the range of four - eight per cent increase in size reduction efficiency.

Jan 1, 1993

The use of coal as a fuel for heat and power generation has a long history. During the nineteenth century most of the present combus- tion technologies were pioneered, as shown in Table 1, This period was associated with the "golden age" of coal and its contribution of almost 80% of the world's energy demands in the early,1900s . The decline in the use of coal has been due to the transfer of the heavy transportation area to diesel power, the elimination of coal as a household fuel and the substitution of oil for coal in power plants. Coal remains the major fuel for the electric utility industry and the present paper will be concerned primarily with that application. Table 1 outlines the development of coal tech- nology with the parallel understanding of coal as a material and its behaviour during combus- tion. Clearly many developments in combustion technology have occurred in this century, although most of the processes had been invented in the nineteenth century. Also, the great expanse in coal research of the past few decades has led to a greater understanding of the coal combustion process.

Jan 1, 1987

Synthetic seismograms of reflectivity method and some field records available are studied to detect the amplitude anomalies at the interface of the gaothermal reservoir the gas and/or oil boundary, and the underground tunnel. The first arrival of PO wave on the P-SV record are weak and emergent while those of P wave only rotated with respect to an incident angle are clear. This can, be explained by means of the energy loss of P-SV wave conversion. The primary reflections of P waves about depth fade away as compared to SH waves which do not perform any conversion, although they hold high attenuation in the fully saturated fluid layers. Reflection of comparable strength is present at the P-wave and S-wave... boundaries, but gas-saturated zones correlating with P wave bright spots do not show equivalent attenuation anomalies. Thus the comparative technique of P-SV wave and SI i wave records is very useful to indicate the strong amplitude anomalies at the boundaries of sealing targets.

Jan 1, 1990

By G Huggins

Excavation in underground jointed rock masses creates cavities into which the surrounding rock mass deforms. Deformations, besides intact rock deformation, include mechanistic deformations such as slip and rotation. In this paper deformational moduli were measured for prototype and blocky (jointed) models using elastic analogue methods for stopes from MIM LimitedÆs Lead Mine. The blocks for the models were defined in terms of the prototypeÆs joint sets, their spatial separations, orientations and average friction characteristics. From dimensional analyses, a relationship between prototype and model deformations was used to predict stope mid-span deformations. The results of this physical modelling work, conducted in the 1970s, motivated an investigation into the electro-treatment of tailings backfill to achieve improved strength and stiffness characteristics. Tailings backfill containing fines and having a high clay content can be electrically dewatered, and at times grouted, cemented, ion exchanged or agglutinated, to achieve relatively high magnitudes of strength and stiffness. These treated tailings stiffnesses can reduce the deformation magnitudes within a rock mass and, in doing so, reduce problems encountered in mine pillar extraction. The application of these tailings modification techniques is examined in relation to the elastic analogue methods.

Jan 1, 1998

By V Salamakha, K Tang, G Si, J Oh, X Wu, Z Yu

The development of machine learning (ML) algorithms has led to promising advances in lithology classification from geophysical logs, which is indispensable in various underground engineering applications. Due to the resolution and availability of logging data, ML models can recognise lithology change in a definitive form at a fine scale (0.01 m). While the results from previous models indicated promising performance in the classification, the robust capability of generalising lithology prediction to unseen data may not be true for those models due to: (1) data bias caused by borehole selections, and (2) logging data mismatches among boreholes. To this end, this paper aims to investigate the generalisability of ML models and seek potential improvements. Four ML models were selected to be trained on single reference boreholes to test the other (as unseen) in the same region, which includes Support Vector Classifier (SVC), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and Residual Neural Network (ResNet10). The data set involves 11 boreholes from a coalmine in north-western Bowen Basin (Queensland, Australia): density, gamma ray, neutron, and sonic logs are selected as inputs. Additionally, a data adaptation method is applied for better generalisability. The results show that there is an accuracy trade-off between the same borehole and unseen boreholes across the models. It also indicates a 16–43 per cent reduction in model performance when generalising the predictions (in marco-F1 score), while the adapted data sets can contribute to a around 12 per cent improvement. This study provides a fundamental understanding of the model generalisability when using a single borehole, essential for further correlating boreholes for regional lithology classification; the adaptation method can improve the generalised accuracy, and reduces the labour to label lithology, which facilitates the identification of gas storage mechanisms, geological/geophysical modelling, and stratigraphic analysis.

Sep 1, 2024

By Holliday RJ

The Imperial Smelting Furnace (ISF) was developed in Britain during the 1950's as a process which could produce zinc from a blast furnace. Since then it has evolved into an efficient means of producing zinc and lead from lower grade raw materials, both of primary and secondary origin. These changes have been in response to the need to improve the cost competitive position of the ISF in a climate of decreasing metal prices. The improvements at the Cockle Creek smelter of Sulphide Corporation Pty Limited have resulted from work undertaken in four main areas: 1. Changes in plant design and operating practice to give more stable furnace operation. 2. Improvements to the quality of sinter being charged to the furnace. 3. Improved monitoring of process variables and the formulation of control strategies based on the improved data. 4. Increased understanding of the processes occuring within the furnace shaft to allow predictive modelling to be undertaken. Work in these areas is still progressing but the work to date has resulted in a significant improvement in the production rate and efficiency of operation.

Jan 1, 1984

By T Sasaoka, H Shimada

Mined-out limestone/aggregate quarries in Japan contain many high and enormous pit walls. Many precious resources are abandoned in these final pit walls. In addition, there are many mines which are located in or near populated areas in Japan. Utilisationof the potentially useful under- ground space at mined-out sites is a topic relevant to the practice of surface mining. This paper describes and discusses the concept of underground space utilisation and tunnelling systems, referring specifically to geotechnical/ tunnelling parameters.

Jan 1, 2008

By M Hino, D R. Swinbourne

The thermodynamic properties of arsenic in metal, speiss, matte, slag and gas phases are first summarised in this paper. Arsenic associates with sulphide minerals and generally has compounds of high volatility, but it has a weak affinity for sulphur and a strong affinity for metals, especially copper and iron. In the initial stage of the oxidation of sulphide concentrates arsenic is volatilised easily prior to the oxidation of FeS, although it tends to be fixed in the condensed phase as FeAsO4 if the concentrate is over-oxidised. Thermodynamic simulation of oxidative copper smelting reveals the distribution of arsenic between matte, slag and gas, and the possibility of condensation of arsenic from the resulting waste gas is discussed. In reductive smelting more arsenic remains in the metal or matte, and is sometimes concentrated as a separate speiss phase. The phase relations and thermodynamic properties of speiss are also summarised briefly. Arsenic refining from smelted copper metal is shown, from an examination of the basic principles of arsenic removal into slags, to be difficult. Owing to its weak affinity for lead however, arsenic refining from lead bullion is seen to be much easier.

Jan 1, 2000

By Penney B. K, Baghdadi A. A

An electron probe micro-analyser, controlled by a dedicated mini-computer,has been operating at Imperial College since 1970. The data assessment capability of the computer was limited and, in order to make better use of the information produced by the analyser, extra computing facilities were needed. Following the initiation of a Laboratory Automation Project at Imperial College involving the use of a central computer linked to laboratory type computers and to further more powerful systems,it became possible to carry out much more detailed and extensive mineralogical analyses by connecting the mini -computer to the Laboratory Automation Network. The paper describes the techniques employed including hardware, software, inter- connection, analysis and operating methods.

Jan 1, 1977

By S C. Sc, J Young, N Belluz, D Nicholas

The heavy sulfide zone (HSZ) of the Grasberg deposit has the geometry of a funnel and is located at the contact of the mineralised intrusive and the relatively barren sedimentary rock types. The geometry and the rock properties associated with the HSZ plays a significant role in pushback design and sequencing. Most of the HSZ has relatively low strengths which must be considered in slope design and management. This paper presents the open pit mine geotechnical and planning design considerations associated with the HSZ.

Jan 1, 2007

By A Melkumyan, M Balamurali

Geological domains describe the mineralisation state and stratigraphic location of different geological regions of mines. They play a very important role at the geological modelling stage as weight percentage of chemical elements information within each geological domain is assumed to be correlated while information coming from different geological domains is considered uncorrelated. Having correct domain assignments to both the chemical assays and the 3D space of modelling is critical for building a reliable geological model of the mine.As standard practice significant effort is invested into the interpretation of the deposit and identification of the geological domains for the chemical assays and the 3D geological space. Despite these efforts, there are some chemical assays with ambiguous geological domain where the exploration assay domain and the block domain do not match. Incorrectly including a sample in the wrong domain can cause a large change in the predicted weight percentage of chemical elements estimation for that block. Therefore, the major challenge of grouping the spatially correlating weight percentage of chemical elements is how to determine which of these domains best fits these misclassified samples.This work proposes machine learning based autonomous technique for identifying to which geological domain (the exploration assay domain or the block domain) the misclassified sample belongs. The proposed methodology is based on Gaussian Process (GP) classification. The GP machine learning approach consists of training and inference stages. At the training stage the GP automatically learns the properties of different geological domains using the chemical assays with unambiguous domain assignment. Then, at the inference stage the GP makes predictions for the geological domains of the assays with ambiguous initial domain assignment.We tested the proposed technique by conducting a case study for an iron ore deposit located in Western Australia. The results demonstrate that the application of the proposed GP technique removes statistically significant deviations in the assay values in many regions: mineralised ore region, unmineralised region, highly weathered region and intrusive material that is highly variable. In this case study the proposed methodology autonomously identified the geological domains for more than 50 per cent of samples which are initially ambiguously classified. For the majority of the assays the GP predicted domain agrees with the geological domain assigned by the exploration assay.CITATION:Balamurali, M and Melkumyan, A, 2014. Automated identification of geological domains for exploration assays with ambiguous initial domain assignment in an iron ore deposit, in Proceedings Ninth International Mining Geology Conference 2014 , pp 99–106 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 18, 2014

By Hamilton TM

The Holocene Minninup shoreline is a coastal barrier system stretching from Bunbury to Busselton, in southwestern Australia. It has developed in a microtidal swell wave environment, under the influence of the post- glacial marine transgression and Holocene sea level variation. Barrier sediments thin rapidly across a shallow shelf, and consist of quartzo-felds- pathic sands with a minor skeletal carbonate component. Holocene shelf deposits are laterally extensive sheets overlying Pleisto- cene limestone. Modern carbonate production is small. Development of the Minninup barrier system has been controlled largely by low rates of sediment input from terrigenous and carbonate sources, late Holocene sea level fluctuati,.,s, and pre-existent coastal landforms composed of Pleistocene limestone. Modern controls on sedimentation are the refracted, shoaling swell wave regime, and onshore winds, which combine to promote nett northward longshore drift. Holocene barrier systems of the southern Swan Coastal Plain are of several different types. These include prograded sequences of beach ridges overlying shoreface sediments, such as is found at Rockingham and parts of Geographe Bay, and complex polygenetic systems typified by the Leschenault Peninsula. Pre- liminary investigations of the barrier stratigraphy of the Minninup shoreline indicate that both progradational and polygenetic sequences are present. The processes involved in shoreline development and heavy mineral accumulation are being studied using aerial photograph inter- pretation, beach profile monitoring, sampling, and granulometric analysis. This will lead to an enhanced understanding of the mechanisms of heavy mineral accumulation, and assist in the development of genetic models as aids for Exploration.

Jan 1, 1986

By S Brochot

In cases where coarse gold is present in a deposit, it is usual to use the screen fire assay (SFA) method to analyse the samples. There is no doubt that this method is more accurate than the standard fire assay (FA) and reduces the risk to have a systematic bias. Nevertheless, the difference between the analytical errors of both methods can be glossed over when the overall sampling error is added to obtain the measurement error. In that case, the advantage of the SFA cannot justify its higher cost.The current paper attempts to address this question in the case of a gold ore deposit with visible coarse gold in various sampling situations (drill core sampling in exploration, blasthole or chip sampling in mining exploitation). The overall measurement error is estimated taking into account the analytical error and all the sampling error components following the Pierre GyÆs theory of sampling.Firstly, only the last sampling stage is considered when the pulverised sample is processed either to obtain one analysis sample for a FA or to be screened and subsampled for a SFA. The calculated measurement error clearly shows the advantage of the SFA specifically in presence of coarse gold. Secondly, the half core sampling is studied to explain the observed discrepancies when controlling the second half core. Finally, the blasthole sampling is treated using in situ heterogeneity models to show that the relative advantage of the SFA is hidden by the large overall sampling error.In conclusion, the choice of the assaying method is discussed at the light of the overall measurement error and in accordance to the analysis objective.CITATION:Brochot, S, 2012. Standard fire assay or screen fire assay? Application of the overall measurement error approach to choose the most appropriate method, in Proceedings Sampling 2012 , pp 135-142 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Aug 21, 2012

Since the 1970s we have seen a marked corporate response in terms of the environment. In part this has come from regulation but it has largely come from stakeholders and the community. We now see a similar trend towards sustainability. The Brundtland (1987) definition of sustainable development provides a direction for advocates: the advance of human prosperity in a way that does not compromise the potential prosperity and quality of life for future generations. In my view its three essential components are: economic, environmental and community. The Global Mining Initiative and the contributions to the Rio World Summit and the Johannesburg World Summit on Sustainable Development indicate that sustainability is being taken very seriously by the mining industry. But does the minerals industry really embrace sustainability as they claim? There is a view that in reality sustainability is a non-event and that the triple-bottom line approach is only a convenient catch-cry for companies who are actually focussed very strongly on the economics part of the equation. Chemical engineers are showing a strong trend to more sustainable practices and the chemical industry has shown real commitment to research into developing sustainable processing systems. This requires a framework for thinking and design and the chemical industry is demonstrating true innovation as it moves towards æno wasteÆ technologies. Whilst there are limits to the rates of change that can occur the minerals industry should also be moving in a much more determined manner towards the notion of processing of products designed for whole-of-life cycle û with minimum/no waste. But is the minerals industry just paying lip service to the importance of research to sustainability?Several common themes influence the science and innovation agenda in Australia, which will affect the development and adoption of innovations by AustraliaÆs minerals sector. First is the well-proven link between peer-reviewed scientific excellence and commercial application. Second is the rise of multi-disciplinary Mode 2 research, which has developed in response to the complexity of problems faced by contemporary researchers, which are best analysed by combining expertise from two or more disciplines. Successful innovation outcomes, in any field, including minerals processing, is promoted by Mode 2 research which benefits from greater levels of networking and collaboration. Kofi Annan in his Message to the World Social Forum puts it very succinctly æThe way forward lies in finding constructive solutions togetherÆ.

Jan 1, 2004

By Z Zhao

Coal dust is hazardous to underground coal workers and water spray is the most common and economic method for controlling coal dust. Previous studies proved that the addition of surfactants can improve the performance of water spray on coal dust suppression. The evaluation methods for surfactants vary from different studies. The zeta potential test is a common method for evaluating surfactants with ionicity. Generally, the suspension of coal dust with pure water usually showed a negative value of zeta potential. The addition of cationic surfactants can increase the zeta potential to a positive value with a small dosage, while the addition of anionic surfactants can only lower the zeta potential. However, there is a lack of comprehensive study to investigate the relationship between the zeta potential and the suppression performance for coal dust. The aim of this study is to reveal the consistency and discrepancy between the zeta potential and the suppression efficiency of a surfactant. Firstly, the mixture of cationic surfactant solutions and coal dust would be evaluated by the zeta potential test. The wind tunnel tests would then be conducted for the same surfactant solutions to measure and calculate the suppression efficiency. It was found that the addition of surfactant can increase the zeta potential and the suppression efficiency and it reached the greatest efficiency when the zeta potential approached to zero. The equilibrium of zeta potential can benefit the suppression performance of surfactants in the wind tunnel test. The result of this study can achieve a better understanding of the mechanism for coal dust suppression. The selection of surfactants will also be suggested for researchers or industries in terms of coal dust control. It would be more economic if a similar performance could be achieved by less consumption of surfactants.

Oct 12, 2022

By E Vargas, A Egana, M Alarcon, X Emery, A Barberan, A Lopez, N Morales, C Friedrich

"As the cost in time and money of data from sensors and small-scale tests has reduced, additional challenges have arisen. Although many mine data sets are not big relative to those in other disciplines, they are complex in other ways, and becoming too large to manage efficiently on personal computers. In order to take advantage of the opportunity offered by increased data, a diverse team from Universidad de Chile and CSIRO Mineral Resources has developed a virtual geometallurgical laboratory to support the computational requirements linking data acquisition with data-driven business decisions. A particular focus to date has been the development of user-guided workflow ensembles to enable comparison between plausible geometallurgical hypotheses.A case study has been undertaken using publicly available data from the Rocklea Dome iron deposit in Western Australia. A hypothetical mining schedule was produced from geochemical and hyperspectral drill core/chips data via the following steps: data preprocessing, exploratory data analysis, geochemical interpolation, block modelling, ultimate open pit design and scheduling. The key outcome of this study was the integration of workflow stages through new plug-in methods or modification of existing software. Outcomes from this study will be described in the paper in terms of geological and metallurgical data quality, analytical software support and ongoing computing infrastructure requirements.CITATION:Lopez, A, Barberan, A, Alarcon, M, Vargas, E, Ortiz, J, Morales, N, Emery, X, Egana, A, McFarlane, A and Friedrich, C, 2016. Progress towards Data-driven Mine Planning via a Virtual Geometallurgical Laboratory, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 287–294 (The Australasian Institute of Mining and Metallurgy: Melbourne)."

Jun 15, 2016

By Johnson N. W, Manlapig E. V, Alexander D. J, Franzidis J. P

The importance of the froth region on flotation performance is often emphasised in the literature. It is well-known that decreasing froth depth or increasing air flowrate results in increasing cell recovery at the cost of lower concentrate gra

Jan 1, 1997

By C Xu, B Li

Multi-sensor fusion visual perception technology significantly enhances visual perception capabilities in complex and harsh environments by combining visual data from different sensors. This technology is especially useful for scenarios where traditional single visible light sensors, such as standard cameras, struggle due to poor lighting, adverse visual conditions, or other visual obstructions. In environments with low light, smoke, or dust, the performance of conventional visible light sensors degrades, limiting their application. By integrating data from various sensors like radar, infrared thermal imaging, and others, multi-sensor fusion technology provides a more comprehensive and complementary visual solution. This fusion not only enhances the robustness of visual systems but also greatly expands their potential applications in fields like visual surveillance. In recent years, deep learning methods have become the mainstream technology for addressing multi-sensor fusion issues, demonstrating significant advantages in adaptive feature selection compared to traditional machine learning methods. However, deep learning-based multi-sensor fusion algorithms still face several challenges. The design of network structures is often redundant, lacking effective screening of useful components within multimodal information. Mainstream fusion algorithms focus excessively on improving display effects without adequately considering the needs of downstream applications and tasks. Existing fusion perception algorithms are generally designed for open visual scenes and lack targeted design for complex visual degradation factors present in tunnel environments of mines. Current deep learning methods for designing multi-sensor fusion networks heavily rely on manual experience to create fusion modules. This reliance increases the complexity of network design and can lead to redundancy. Redundant network modules are difficult to identify in end-to-end learning tasks at this stage, significantly slowing down network inference and potentially interfering with the output of fusion perception. Additionally, training these fusion modules typically requires large amounts of well-annotated multimodal data, further increasing implementation difficulty and cost. For instance, the fusion network design proposed by Li and Wu (2018) focuses on extracting multimodal fusion features, while Zhao et al (2020) introduced a feature decomposition mechanism in the feature fusion and extraction modules. Researchers like Zhang and Ma (2021), Xu et al (2020), and Liu et al (2017) have attempted to improve network structures through dense cascades and the introduction of residual connections. Although these methods have improved the handling of multimodal information to some extent, they still face limitations in distinguishing between useful and redundant information, with redundancy persisting in network designs. Ideally, the design of fusion networks should be more intelligent, guiding network structure design heuristically based on the importance of different modal information for the current task. This would reduce information redundancy and network weights, requiring the development of new algorithms or frameworks capable of automatically identifying and optimising fusion strategies, thereby reducing dependence on manual experience while improving fusion efficiency and network performance. Current deep learning designs for multi-sensor fusion algorithms often overlook the

Sep 1, 2024