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By M. Kumral, S. Hmoud

Optimising the configuration of infill drill holes is an important step during mineral exploration campaigns. However, this optimisation process encompassing all possible drilling configurations within a mineral deposit is highly combinatorial and hard to solve in a reasonable time. This paper proposes using spatial clustering algorithms to divide the orebody into contiguous zones and target the best zones with infill drilling in order to reduce the size of this optimisation problem. Several clustering algorithms are assessed in a spatial context on hypothetical datasets. This evaluation shows that the hierarchical density-based spatial clustering application with noise (HDBSCAN) algorithm can be used in combination with the uniform manifold approximation and projection (UMAP) dimensionality reduction algorithm to identify contiguous zones in the orebody.

Sep 1, 2021

By Sathyaprasad Nanjundaiah

The Paper intends to showcase a framework for spatial data collaboration from multiple sources of data, in order to create a single source of truth across the Organization. The framework is targeted to reduce the data duplicity, re-work, time loss due to search of required data and hindrances to fetch or transfer data from various data sources. The spatial data collaboration will provide a single window view of the entire organization with respect to its operations, management, sales, customers and competitors on a spatial reference across various regions in the World. Large Organizations with cross-country operations can standardize the use of spatial data through this framework for ease of data access, increasing the data reliability / integrity and better / on time decision making. Keywords: spatial data, GIS, collaboration, framework, mining, ESRI, tab files, shape files, ETL, reliability, integrity, interoperability, geo data, geo database, single source of truth

Sep 1, 2012

By A. Wadood M. A. El Rabaa, William A. Hustrulid, William F. Ubbes

The spatial distribution of the deformation modulii around the CSM/ONWI test facility was determined using an NX version of the CSM cell. Approximately 840 modulus measurements were made in six rings (each ring containing seven holes each 6 m in length) of boreholes. These parallel rings were spaced at 2.4 m intervals along the room. Contour plots of the modulii revealed that the depth of the blast damage zone varied both with perimeter position and distance away from the opening. The maximum depth of disturbance appeared to be of the order of 60 cm. At locations removed from the opening, the variability in modulus was quite high reflecting the presence of joints, faults, shear zones and foliation. A comparison of rock mass modulii (ER) with those obtained from the laboratory testing of core (E), revealed that ER [=] 0.5 E.

Jan 1, 1982

By J Penman, N Turner, H Liu

This paper aims to present a snapshot of the risk profile for tailings storage facilities within Western Australia by comparing the spatial distribution of known facilities against common geohazards such as cyclonic activity, climate, and peak ground accelerations from earthquakes. The analysis also includes an assessment of proximity to populations at risk including towns and sensitive receptors including significant river systems and wetlands.

Jul 1, 2021

By N J. Potter, N W. Brand, J M. F Clout

The increasing demand for iron ore with low concentrations of trace elements, puts increasing pressure on iron ore producers for high-quality material. Understanding the mineralogy, petrography, chemistry, and mineral association of iron ore deposits is becoming increasingly important to provide iron ore products that meet the ever-increasing standards of steel mills. Limited attention has been paid to documenting new orebodies beyond bulk RC drill chip assays and product specification data. Therefore, limited information is known about the spatial distribution of minor and trace elements at the hand specimen scale, and elemental deportment within different ore and gangue minerals. In this study, samples from high-grade microplaty hematite, supergene-enriched martite-goethite and hematite iron ores are examined for their elemental and mineral associations. These samples contain distinctive minor and trace element distributions, with the mapping of deleterious elements (eg Zn, As, Cu) enabling the deportment and abundance within the ore and gangue minerals to be assessed. Results from this study show a diverse range of minor and trace mineralogy that are present in typical iron ore samples, in abundances below the detection limit of routine XRD scans, that host the deleterious elements, including but not limited to, sphalerite (Zn and S), chalcopyrite (Cu and S), xenotime (P and Y), apatite (P and Ca), cryptomelane (K and Mn), barite (Ba and S), alkaline feldspar (K, Al and Si) zircon (Zr and Si) and chromite (Cr and Al). The presence of these minerals and associated deleterious elements, even at low concentrations, has implications for producers, with the ongoing restrictions and tightening of environmental constraints in shipped iron ore products. By understanding the distribution and location of these elements within the iron ore, steps can be considered to maintain increasingly higher quality iron ore supply around the world.

Nov 8, 2021

By Parviz Montazer, Robert King, William Ubbes, Gideon Chitombo

This paper describes the results of a detailed study that was undertaken to define the spatial distribution of permeability within a five meter thick envelope around the CSM/ONWI room. Detailed fracture orientations and distribution were determined through mapping of the walls of the opening, logging of oriented core, and visual examination of borehole walls with a borescope and a T.V. camera. Over 3,500 measurements were made from which the three dimensional distribution of fractures was determined. Two principally different testing equipment designs and various methods of air injection tests were used in all boreholes to identify and characterize conductive fractures. Through analizing the distribution of permeability and fracture index around the room a zone of blast damage of approximately .5 m thickness was delineated. The effect of stress modification seems to extend farther into the host rock to approximately 3.5 m depth.

Jan 1, 1982

By F. E. Steffens

The application of kriging in assessing the area rainfall in a weather modification experiment is complicated by the presence of many zero rainfall recordings on a given day, and the fact that the variograms seem to be quite different for the rainfall on different days. Indicator variograms are shown to be directly related to two sets of conditional probabilities. Probability kriging is used in estimating the probability of rainfall amounts above any cutoff at any point

Jan 1, 1987

By Khoi Nguyen, Keeney. Luke

An outcome of geometallurgical mapping and modeling is the generation of continuous down hole profiles of quantitative geometallurgical attributes at assay scale. These attributes vary from traditional routine data collection methods such as assays and geotechnical logging (e.g. RQD, Fracture Frequency), to new measurements including petrophysical attributes, EQUOtip hardness data and modelled estimates of metallurgical performance indices (e.g. A*b, BMWi). Highly variable continuous geometallurgical data with high spatial resolution can make it difficult to identify spatially continuous domains. An automated method based on the well known time series analysis technique of cumulative summation (CuSum) has been developed which uses statistical analysis to identify domain boundaries in down hole profiles. A bootstrap analysis automatically identifies potential domain boundary locations with associated confidence levels and a series of t-tests determine the significance of defined populations. A hierarchical clustering algorithm is applied to results to enable data sensitivity to be taken into account. The method produces statistically significant populations and is suitable for application on either single or multiple drill hole datasets. Domains defined preserve the inherent variability of the continuous down hole data and provide a method for scaling up variability data (i.e. assay interval scale) to mine scale (i.e. bench scale, block model). A major advantage of the method is its ability to provide suitable input parameters for use in spatial modeling of non-additive and non-linear geometallurgical attributes through conditional simulation techniques.

Jan 1, 2014

By Mustafa Kumral, Samer Hmoud

Effective management of ore loss and dilution is essential for successful grade control and short-term mine planning due to their significant impact on the economic, environmental and technical aspects of openpit mining operations. Factors influencing ore loss and dilution fall into two categories: (1) controllable factors, like mine equipment selectivity and blast design, and (2) uncontrollable factors, such as spatial heterogeneity of ore and waste blocks on a bench. This paper focuses on the second category by applying spatial entropy concept to capture heterogeneity at the scale of selective mining units. In this paper, global spatial entropy is used to assess the impact of spatial heterogeneity between ore and waste blocks on the magnitude of ore loss and dilution, while the local spatial entropy can guide the allocation of blast movement monitoring balls preblast. High values of the global spatial entropy indicate increasing potential of ore loss and dilution, which reduce profit. Furthermore, through a number of case studies, the study investigates the relationship between spatial entropy, cutoff grades, blast movement, dig-limits optimization model running time, and profit. The results show that changes in cutoff grade and blast movement can significantly affect spatial entropy post-blasting and increase ore loss, dilution and profit reduction, revealing the need for controlled blasting at specific bench sections. Additionally, the results demonstrate an exponential increase in profit reduction due to ore loss and dilution with a rising global spatial entropy

Jun 1, 2024

By Mustafa Kumral, Samer Hmoud

Effective management of ore loss and dilution is essential for successful grade control and short-term mine planning due to their significant impact on the economic, environmental, and technical aspects of open-pit mining operations. Factors influencing ore loss and dilution fall into two categories: (i) controllable factors like mine equipment selectivity and blast design and (ii) uncontrollable factors such as spatial heterogeneity of ore and waste blocks on a bench. This paper focuses on the second category by applying spatial entropy concept to capture heterogeneity at the scale of selective mining units. In this paper, global spatial entropy is used to assess the impact of spatial heterogeneity between ore and waste blocks on the magnitude of ore loss and dilution, while the local spatial entropy can guide the allocation of blast movement monitoring balls pre-blast. High values of the global spatial entropy indicate increasing potential of ore loss and dilution, which reduce profit. Furthermore, the study investigates the relationship between spatial entropy, cut-off grades, blast movement, dig-limits optimization model running time, and profit through a number of case studies. The results show that changes in cut-off grade and blast movement can significantly affect spatial entropy post-blasting and increase ore loss, dilution, and profit reduction, revealing the need for controlled blasting at specific bench sections. Additionally, the results demonstrate an exponential increase in profit reduction due to ore loss and dilution with a rising global spatial entropy.

Nov 28, 2023

By Qiang Wang, Jiaqiang Yu, Chunhui Fan, Yong Wang, Changyu Jin, Jun Bai, Yu Lu

Accurate ore blending necessitates an in-depth understanding of movement trajectories of fragments and the spatial evolution of the displacement field in the bench during blasting, Accurate ore blending is currently one of the most complex challenges faced by mining engineers. In light of this problem, a systematic study was conducted in this paper using neural network and numerical simulation based on field monitoring data. A nonlinear mapping relationship was established between the mechanical parameters of rock mass and the displacements of the monitoring points. The measured displacements of monitoring points under blasting were input into the neural network, which used back-calculation to derive the mechanical properties of the rock mass. These parameters were then applied in a forward calculation to analyze the movement trajectory of the monitoring points. The results showed that the calculated displacements were in good agreement with the monitoring results during the. The average relative errors in the horizontal and vertical displacements were 4.12% and 15.2%, respectively. Furthermore, the muckpile profile was in an inverted recumbent “S” shape after bench blasting, which was consistent with the actual shape of the muckpile. This verified the rationality and accuracy of the method proposed in this study. Finally, the movement trajectories of particles in the bench and the spatial evolution law of the displacement field during bench blasting were determined based on the calculation results, offering theoretical support and fundamental information for accurate ore blending.

Dec 16, 2023

By M J. Newton

As part of the AMIRA P843 project Keeney and Walters (2008) describe how the principal components analysis (PCA) method can be used to identify classes of samples with similar metallurgical characteristics. However PCA does not take account of the location of each sample in 3D space. This paper describes a study to analyse the spatial distributions of the classes and determine appropriate modelling methods to control the estimation of the comminution parameters and mill performance indices into a 3D block model. This includes but is not restricted to geostatistical techniques that are used for grade modelling. The starting point for the study is the class definitions and the regression models for estimating the comminution parameters and performance indices. Each sample is assigned a class and the spatial distribution of each class has been analysed using different techniques including the calculation of variograms. This establishes whether the classes can be used as domain control for estimation into the block model – a procedure similar to using geological rock type domains for controlling the estimation of grades for a resource model. However, standard geostatistical estimation methods such as ordinary kriging assume that the variable being estimated is additive or linear. This assumption is valid for variables such as grade but this is not necessarily the case for the comminution parameters or the performance indices. Therefore the estimation procedure must either use variables that are definitely additive or the effect of potential non-additivity must be tested and accounted for where possible.The results of the study show how performance indices such as recovery, throughput and specific power can be estimated into the block model. This model is then combined with the geological model to provide a multi-parametric model that is used to optimise the mine planning and scheduling activities which can lead to significant improvements in NPV.

Sep 5, 2011

By K. J. Palmer, D. A. Silva

"Evaluating resources and reserves requires the reliable modelling of geological domains and their grades. “Multiple point statistics” simulation is a relatively new geostatistical method to generate complex, high-resolution geological models by extracting high-order spatial relations from training images. A method based on combining multiple training images is developed to obtain the correct amount of large-scale continuity and short-scale variability. A calibration process matches the geological spatial variability between the final realizations and the drillhole dataset. A case study with data from the Red Dog mine, Alaska, United States, shows an appropriate reproduction of short-scale variability along boundaries between geological units.RÉSUMÉ L’évaluation des ressources et des réserves exige une modélisation fiable des domaines géologiques et de leur teneur. La simulation par « statistique multipoint » est une méthode géostatistique relativement nouvelle pour générer des modèles géologiques complexes à haute résolution par l’extraction de relations spatiales d’ordre supérieur à partir d’images d’entraînement. Une méthode basée sur la combinaison de multiples images d’entraînement est développée afin d’obtenir la bonne quantité de continuité à grande échelle et de variabilité à petite échelle. Un processus d’étalonnage fait correspondre la variabilité géologique spatiale entre les réalisations finales et l’ensemble des données de forage. Une étude de cas avec des données de la mine Red Dog, Alaska, États-Unis, montre une reproduction adéquate de la variabilité à petite échelle le long des limites entre les unités géologiques."

Jan 1, 2015

Mechanical and electrical (M&E) systems in road tunnels are constrained by the traffic envelope and the construction profile. Whilst these spatial constraints are often ælocked inÆ early in the design process, the detailed M&E design continues for some considerable time after key civil engineering issues have been resolved. Ventilation design criteria for both normal and emergency operation often involves considerable negotiation with a wide range of stakeholders. Final system performance and spatial requirements are only finally resolved when suppliers are selected following the tender process. Lighting design is dependent upon a wide range of factors including tunnel lining materials and associated colours as well as agreed maintenance regimes. Cabling systems can only be developed when the general arrangement for power distribution is agreed and a system of substation, switchrooms and equipment rooms is in place. Many other systems such as fire protection and communications facilities fill the available space beyond the traffic envelope, where physical, structural and æsight lineÆ requirements must all be accommodated. The more co-ordinated civil engineering and M&E design is and the earlier the process starts the better the outcomes for all parties.

Jan 1, 1999

By A. Hekmatnejad

"The objective of this work is to validate a methodology for spatially predicting the fracture intensity, defined as the average fracture area per unit volume. First, using the observations from drill holes, the fracture intensity is directly inferred at the support of drill-hole composites based on a Terzaghi correction. Subsequently, the composite values are interpolated to larger blocks. The methodology is tested on sets of simulated fracture networks, in which each fracture consists of a disc with a random diameter, random position and random orientation. For each of these simulated networks, one can calculate the actual fracture intensity within any region of space, based on geometric considerations. A regular sampling mesh is then defined to emulate a set of vertical drill holes and the proposed methodology is applied to predict the fracture intensity, both globally and locally. The actual and predicted fracture intensities are finally compared, showing that predictions are unbiased, insofar as, on average, the prediction error is always close to zero. Also, the error dispersion increases when the support of the prediction decreases, which is consistent with the well-known support effect. In practice, the proposed methodology allows predicting fracture intensity based exclusively on drill-hole information, without the need for simulating fracture networks in space, hence its interest. INTRODUCTION The characterization of fractures in rock masses is an important part in the evaluation of mechanical and hydraulic properties of rocks. Fractures have a large impact in disciplines such as reservoir engineering, safety of underground storage of CO2 or of nuclear waste, assessment of high-enthalpy geothermal installations, safety of mining exploitations, efficiency of in-situ leaching operations or of extraction by block-caving. As a rock mass property, fractures must be characterized in the three-dimensional space, whereas observations are limited to 1D (drill holes) and 2D (outcrops, drift walls), moreover very often to rather short stations, so that the available data are subject to geometric bias, truncation and censoring. Fracture characteristics includes the number of fracture sets and, for each set, the number, orientation, spacing, location, shape and size of the fractures must be inferred from data sampling. Some important parameters that are considered nearly in all models are fracture intensity and fracture size."

Jan 1, 2016

By John P. Albers

During the 1950's and 1960's a program of geologic mapping of counties has been underway in Nevada by geologists of the U. S. Geological Survey and the Nevada Bureau of Mines. The aping has been done principally at reconnaissance scales, with more detailed work in local areas. Geologic maps are either published or open-filed for about a dozen counties at scales of 1:200,000 or 1:250,000. One by-product of the geologic mapping has been the recognition of about 80 Tertiary volcanic centers from which large or very large volumes of volcanic material ranging from rhyolitic to andesitic in composition have been erupted. For purposes of this discussion these are regarded as the major centers; the tally does not include hundreds and perhaps thousands of small rhyolitic domes and plugs and basaltic vents. About 15 to 20 of the 80 major centers are believed to be calderas ranging in diameter from 3 to 25 miles. Some have been described in the literature by geologists of the Nevada Test Site and others. However, the vast majority of the 80 centers have not been described in print, and we are indebted to our colleagues for locating them for us in many of the counties. Briefly, we would like to express our appreciation to the following people all members of the USGS unless identified otherwise: Robert Coast, who has identified the centers in Elko County; Ron Willden, Robert Yates, and

Jan 1, 1968

The statistical methods described in the previous chapter permit the estimation of the average value p of a deposit, and the calculation of confidence limits for this value. They are based on the assumption of independence of sample values. As soon as a reasonable number of samples has been obtained from a deposit, local valuation, or estimation of blocks of ore within the mineral deposit, becomes necessary. The assumption of independence of values must then be rejected. Local valuation is possible only if there is a relationship between the value of a sample and the value of the surrounding ore, provided this relationship is a function of the position of the sample with respect to the blocks of ore to be valued. Whichever method is used for the valuation of a block of ore, the following assumptions are always made: ? The values of samples located near or inside the block are related to the value of the block. ? The values of the samples located closest to the block are most closely related to the value of the block. These assumptions will hold true only if the following assumption can also be made: ? There exists a relationship between sample values which is a function of the distance between samples. We are saying that the value x (z) of a sample centred at a point z has properties which are functions of this point. A certain spatial structure exists in the sample distribution. We are therefore dealing with a regionalized phenomenon, and we must treat x (z) as a regionalized variable. This can be done statistically by means of a model chosen to represent the spatial structure of the phenomenon. We shall see that the relationship between block values and sample values can be deduced from the relationship between sample values, and all local valuation problems can be solved using the statistical model obtained from the analysis of the sample values. It is important to realize that this statistical model is obtained by analysing the properties of known sample values, and will be used for the estimation of unknown block values. Such a statistical inference is valid only if the model developed represents the properties of both the sampled section of the ore body and the section to be valued: some stationarity conditions must be satisfied, and the model with the least restrictive conditions is preferred. In the following chapters, the most important models used in spatial geostatistics are presented. The models which can be used when there is no significant drift (trends) in values are described in Chapters 3-1 1. These models can also be used to solve some specific valuation problems when a linear drift is present. A general study of the more difficult problem of analysis of an ore body whose values present a drift is described in Chapter 12. Note that the area considered for local valuation of a block of ore is often small enough for any drift which might be present to be ignored.

Jan 1, 1978

By Christopher Mark

Mine planning for a new reserve is based on information obtained from exploratory coreholes. A critical component of an exploration program is the geotechnical evaluation. Poor assumptions about roof conditions greatly add to the risks of mining. Rock mechanics testing is central to a geotechnical exploration program. Typically, 3 to 5 uniaxial compressive strength (UCS) tests are made to characterize a particular roof unit at a given corehole. The average (mean) of these tests is taken as "The UCS" for that location. Isopach contour maps are then used to show spatial trends in roof strength. Two issues are raised by this traditional approach. The first is due to the large variability in UCS values that is typical even within a single unit from a single hole. The average UCS might be higher at Corehole A than it is at Corehole B, but the difference may not be statistically significant. The second issue is whether widely spaced coreholes can identify valid spatial trends in rock strength. The answer depends upon whether rock strength changes over distances that are longer or shorter than the corehole spacing. This is a classical geostatistical problem. While geostatics have been used to investigate many coal quality parameters, they have seldom been used to evaluate rock strength. This paper describes an extensive investigation of these issues conducted by the National Institute for Occupational Safety and Health (NIOSH) in collaboration with Peabody Energy. The study employed the Peabody Rock Mechanics Data Base which contains more than 10,000 individual test results. Data from four important roof units were subjected to statistical analysis: ? Brereton Limestone above the Herrin 6 seam (Illinois) ? Turner Mine Shale above the No. 9 Seam (Kentucky) ? Sandstone above the Eagle Coal (West Virginia) ? Shale above the Eagle Coal (West Virginia) The study did not find significant spatial trends in rock strength in any of the cases. Perhaps there are none, or perhaps the exploration coreholes were just too far apart to see them. These results have valuable implications for the design of geotechnical exploration programs.

Jan 1, 2004

By Deno Pappas, Chrisropher Mark, John Rusnak, Linda McWilliams

Mine planning for a new reserve is based on information obtained from exploratory coreholes. A critical component of an exploration program is the geotechnical evaluation. Poor assumptions about roof conditions greatly add to the risks of mining. Rock mechanics testing is central to a geotechnical exploration program. Typically, 3 to 5 uniaxial compressive strength (UCS) tests are made to characterize a particular roof unit at a given corehole. The average (mean) of these tests is taken as “The UCS” for that location. Isopach contour maps are then used to show spatial trends in roof strength. Two issues are raised by this traditional approach. The first is due to the large variability in UCS values that is typical even within a single unit from a single hole. The average UCS might be higher at Corehole A than it is at Corehole B, but the difference may not be statistically significant. The second issue is whether widely spaced coreholes can identify valid spatial trends in rock strength. The answer depends upon whether rock strength changes over distances that are longer or shorter than the corehole spacing. This is a classical geostatistical problem. While geostatics have been used to investigate many coal quality parameters, they have seldom been used to evaluate rock strength. This paper describes an extensive investigation of these issues conducted by the National Institute for Occupational Safety and Health (NIOSH) in collaboration with Peabody Energy. The study employed the Peabody Rock Mechanics Data Base which contains more than 10,000 individual test results. Data from four important roof units were subjected to statistical analysis: • Brereton Limestone above the Herrin 6 seam (Illinois) • Turner Mine Shale above the No. 9 Seam (Kentucky) • Sandstone above the Eagle Coal (West Virginia) • Shale above the Eagle Coal (West Virginia) The study did not find significant spatial trends in rock strength in any of the cases. Perhaps there are none, or perhaps the exploration coreholes were just too far apart to see them. These results have valuable implications for the design of geotechical exploration programs.

By Jan Rosenkranz, Anders Sand, Lisa Malm, Nils-Johan Bolin

Within flotation technology the general trend is towards very large cells. Scale-up is usually done by postulating geometrical similarity, which implies keeping the aspect ratio constant when increasing cell volume. Consequently, the design of flotation circuits typically involves several cells of identical geometry within a bank. Using a few standard sizes in a flotation plant simplifies design, manufacturing and maintenance of the cells, but does not necessarily guarantee optimal performance and selectivity of the flotation process. Geometry parameters for a given cell volume that influence flotation cell performance include cell height, which causes changes in the hydrostatic pressure and suspension hydrodynamics, and also influences the travel distance of particle-bubble agglomerates as well as the homogeneity of the mixing. Also the thickness of the froth layer depends on the aspect ratio of the cell. The objective of this work is to gain a better understanding of material distribution and properties within a flotation cell and, based on this information, elucidate how alterations of the cell geometry can influence separation efficiency. For this purpose systematic measurements and analyses of the spatial distribution of the different phases within a 160 m3 flotation cell have been carried out with a particular focus on an industrial, low-grade copper ore beneficiation process. The concepts for sampling at different vertical and lateral positions of the flotation cell are introduced. The results from the experimental work give an understanding of internal material distribution within flotation cells. Based on the measured phase distribution and concentrations as well as particle properties at various positions within the cell, the implications for an optimized scaling and design of individual flotation cells within a flotation circuit are discussed.

Jan 1, 2016