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EXPLORATION AND MINING GEOLOGY JOURNAL EMG Quality Assurance, Continuous Quality Improvement and Standards Can Reporting Definitions Substitute for Standards? Forensic Geology and Mineral Exploration Projects Geological Controls in Resource/Reserve Estimation Geology as a Basis for Refining Semi-variogram Models for Porphyry-type Deposits Integrating Geology and Borehole Geophysics in a Common Earth Model for Improved Three-dimensional Delineation of Mineral Deposits The Application of Geophysical Methods to Improve the Quality of Resource and Reserve Estimates Exploratory Data Analysis: A Precursor to Resource/Reserve Estimation Quantitative Estimation of Dilution and Ore Loss Relative Kriging Errors — A Basis for Mineral Resource Classification Sampling Quality Control Practical Quality Control Procedures in Mineral Inventory Estimation Gold Deposits: Establishing Sampling Protocols NUGGET: PC Software to Calculate Parameters for Samples and Elements Gold Analysis — Fire Assaying and Alternative Methods Error Variance Information from Paired Data: Applications to Sampling Theory Evaluation of Errors in Paired Analytical Data by a Linear Model Optimizing the Operational Strategy of a Mine-metallurgy
Abstract—In recent years, several unsavory events in international mineral exploration, as well as several widely publicized project difficulties and failures have occurred. The report Setting New Standards has “raised the bar” and proclaimed a “commitment to continuous improvement... and change.” We need to evolve from our “generally accepted” practices to more effective quality assurance policies, guidelines and standards. Several steps will be required to support the work of the “qualified persons” now wholly entrusted with technical and professional matters:
To regain investors’ confidence and improve the returns from mineral development activities, an explicit commitment to quality by the board of directors and the management of every company is required.
Resource/Reserve Estimation and Inventory: Abstract — Traditionally, the emphasis in ore and reserve inventory has been to provide fairly simple definitions and presentations for reporting to shareholders and the investing public. The recent introduction of the mineral resource category aims to take into account the “part of the deposit that cannot yet be produced or extracted legally and profitably.” Recent proposals still place insufficient emphasis on relating resource/reserve reporting definitions more closely to the needs of mining and exploration operators for the estimation and inventory of these basic material assets. In most schemes, significant ambiguities and shortcomings remain. These concern the potential economic interest of resources, the concept of continuity which is fundamental to the estimation of volumes, mass and grades, the objectives of the production feasibility study and the requirements of the geology, engineering and economic appraisals leading to it, and the “availability” of the permits required to start mine development. Up to now, no industry-wide formal consensus has yet been reached for any of these steps, nor for reconciliation between successive statements. A resource/reserve inventory scheme is presented here that is based on ISO 9000 principles and the Australasian system. Explicit criteria and transition points are proposed to define resource and reserve. Similarly, appropriate criteria are proposed to classify the three mineral resource and two ore reserve categories, based on geological and value continuity and on the objectives of the feasibility study. This scheme offers a way to develop ISO 9001 certification of resource/reserve estimation procedures for mining operations and supply exploration companies with an appropriate inventory system, to allow better information for the shareholders and the investing public. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved. Résumé — L’objectif des inventaires des minerais et des réserves est, depuis le début du siècle, de fournir des définitions simples et d’ordre général visant les actionnaires et le public investisseur. L’introduction d’une catégorie de « ressources minérales » fournira un cadre tenant compte de la “portion d’un gisement qui ne peut encore être extraite ou exploitée légalement et à profit.” Cependant, les propositions récentes de systèmes d’inventaires ne comportent pas des définitions des ressources et réserves qui tiennent compte suffisamment des besoins des opérateurs en exploitation et en exploration minière. La plupart des systèmes comportent des ambiguïtés et des carences. Citons la susceptibilité d’exploitation commerciale des ressources, la continuité qui est au centre de l’estimation des volumes, masses et teneurs, les objectifs de l’étude de la faisabilité de la mise en production, le niveau requis des travaux de géologie, d’ingénierie et d’économique qui y mènent, ainsi que la disponibilité des permis dont dépend la mise en production. Il n’y a jusqu’à maintenant aucun consensus dans l’industrie sur ces points, ni sur des procédures de réconciliation entre les estimations successives. Le système d’inventaire des ressources/réserves proposé ici s’appuie sur la structure ISO 9000 et le système australien. Des critères et des points tournants explicites sont établis pour définir les ressources et les réserves. De même, les définitions des trois catégories de ressources et deux catégories de réserves, s’apparent sur la continuité de la géologie et des teneurs et sur les objectifs de l’étude de la faisabilité. Ce projet offre une voie pour développer les critères de la certification ISO 9001 pour les opérations minières, tout en fournissant un système approprié d’inventaire aux compagnies d’exploration, pour mieux informer les actionnaires et les investisseurs potentiels.
Forensic Geology and Mineral Exploration Projects Abstract — Forensic geology in a mineral exploration context is concerned with geology and related technical matters as they pertain to legal cases involving exploration and evaluation of mineral properties. Such cases involve the possibility of outright scams that include falsification of data and information, as well as inappropriate application of various technical procedures. Experience in forensic geology in such cases emphasizes the need for systematic quality control procedures during routine exploration/appraisal and indicates the need for more attention to ‘target hardening’ (improving security in the chain of custody of samples and assay results). A number of ‘early warning signs’ that might suggest some form of tampering or falsification of information are listed. These measures will support the work of the "Qualified Persons" (geologists and engineers) entrusted with the scientific and technical aspects of mineral exploration, and facilitate the increased attention to regulatory oversight and enforcement of securities laws recommended in the report "Setting New Standards." © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Geological Controls in Resource/Reserve Estimation Abstract—Geology contributes essential information toward obtaining high-quality resource/reserve estimates. In this context, geology can be considered under the following overlapping topics: regional geology, detailed (deposit) geology, mineralogy, ore deposit models and continuity, with geological mapping being fundamental to all. Each of these topics is considered here in terms of potential contributions to “improved” mineral inventory estimation. Some of the principal conclusions are:
Geology as a Basis for Refining Semi-variogram Models for Porphyry-type Deposits Abstract — Two examples are used to describe how geological features impact on the development of semi-variogram models to be used for geostatistical resource/reserve estimation of porphyry-type deposits. In the Main zone of the Huckleberry porphyry copper deposit, mineralization is concentrated in fracture zones localized in volcanic rocks, along the eastern and southern margins of a granitic stock. Mineralized volcanic rocks can be subdivided into three separate domains, each with its own preferred direction of mineralization that is reflected in contoured Cu diagrams and semi-variograms. The East zone at Huckleberry deposit, spatially distinct from the Main zone, is controlled by a fracture zone elongate roughly east-westerly and bounded on the south by a major fault (easterly striking and steeply dipping) across which there is a dramatic drop in grades. The eastern part of the East zone appears to be coaxial with a large intrusive body; the western part contains a small, elongate dike-like intrusion. Contoured Cu values for many levels suggest that the principal direction of geological elongation of the east and west domains of the East zone differs significantly. Independently derived semi-variogram models for each domain are different and reflect this difference in trend. In both Main and East zones of the Huckleberry deposit, block estimates by ordinary kriging are significantly different using a domain-specific semi-variogram model than using a deposit-general semi-variogram model. The domain-specific estimates are deemed better because they are based on local controls of mineralization and have less conditional bias than those generated by the deposit-general semi-variogram model. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Integrating Geology and Borehole Geophysics in a Common Earth Model for Improved Three-dimensional Delineation of Mineral Deposits Abstract —The application of geophysical technology to resource delineation aims to improve the quality of resource/reserve estimates by integrating high-resolution survey methods, geophysical modeling and inversion with three-dimensional representations of geological and mineral deposit data. The use of geophysics can cost-effectively improve a geological interpretation based only on geological and sampling data. Success depends upon the ability to use geological visualization and modeling software, first to develop a three-dimensional geological model and then to modify it interactively by integrating geophysical data with the geological and sampling data. The high resolution required for mineral delineation geophysics results in a focus on borehole seismic and high-frequency electromagnetic methods. Borehole wireline logging is used to develop an understanding of the relationship between physical properties and geological description. Data from core samples and borehole wireline logs allow the construction of a three-dimensional physical property distribution, consistent with the existing geological interpretation. The three-dimensional physical property distribution is used for both geophysical forward modeling (to compare to field data) and as a starting model in iterative inversions. Advanced visualization techniques allow the simultaneous viewing of the three-dimensional physical property model, the geological information and data from which it is derived, and the geological interpretation and the geophysical results. Geophysical results may be simulated responses from a forward model or the output from a numerical inversion in the form of an updated physical property distribution. Iterative refinement of the geological interpretation is required to ensure consistency with the geological and geophysical data. The key to success with this approach is that all relevant geological, geophysical, and rock property data reside in a common, visual model of the earth.
The Application of Geophysical Methods to Improve the Quality of Resource and Reserve Estimates Abstract — Exploration for deep underground copper and nickel sulfide deposits in the Sudbury mining camp is carried out with surface drilling. More detailed drilling, with an advanced underground exploration program, may be necessary to establish an accurate interpretation of the deposit geology and upgrade the resource estimate to the measured category for reserve estimation and feasibility assessment. Resource evaluation is a lengthy and costly process that could result in a decision not to proceed with the project. For projects that proceed to production, significant reductions in the operating and capital costs could be achieved with a more accurate interpretative model of the deposit geology and mineralization. Quality control procedures to ensure the integrity of the drilling data and interpretation guidelines are essential steps in the development of a deposit model. The use of block modeling techniques and the application of geostatistics for resource estimation further improve the quality of the resource model. Significant improvements to the interpretive models can also be achieved by incorporating additional information from geophysical measurements to validate and constrain the geological interpretation. The geophysical models must be consistent with known geological environments and ore-forming processes, which has required the concurrent development of comparative models from exploited deposits. These geophysical techniques can also provide key geotechnical information required for the optimum design of the mining method and mining sequence. The objective of this program is to improve the accuracy of the deposit model and the quality of the resource and reserve estimates in order to optimize capital investments and reduce the development and operating costs of underground mining projects. Several of these techniques are currently being tested at INCO Limited’s Sudbury operations. The results from those tests are presented and their applications are discussed within the framework of resource/reserve classification systems and project evaluation objectives. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Exploratory Data Analysis: A Precursor to Resource/Reserve Estimation Abstract—Exploratory data evaluation is an essential part of every high quality, mineral inventory estimate. Efficient analysis involves a thorough organization of available quantitative data that are the basis of the estimate and perhaps the formation of composite grades. Data organization and evaluation can involve more than 50% of the time necessary to conduct a mineral inventory estimation. The principal purpose of exploratory data evaluation in mineral inventory work is to improve the quality of estimation by providing insight into characteristics of the variables under investigation. Specific aims include: (1) to recognize and eliminate errors; (2) to provide a comprehensive knowledge of the statistical characteristics of all variables of interest for resource/reserve estimation; (3) to document and understand the interrelationships among the variables of interest; (4) to recognize systematic spatial variation of variables such as grade and thickness of mineralized zones; (5) to recognize and define distinctive geological domains that require independent estimation of mineral inventory; (6) to identify and characterize outliers; and (7) to evaluate similarity/dissimilarity of various types of raw data, especially samples of different supports. These aims are not mutually exclusive but they can all have their own impact on resource/reserve estimation. Error must be minimized. Individual variables can have characteristics that lead to different decisions in the course of estimation. Similarly, interrelations of variables might contribute to the ease (or difficulty) with which estimates of several variables can be obtained. Trends can impose the need for two or more domains, each of which might be estimated independent of the others. Outliers, a perennial problem, require detailed evaluations because they impact on reserves much out of proportion to their abundance. Data, of widely different supports, generally must be standardized if all are to be used for purposes of estimation. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Quantitative Estimation of Dilution and Ore Loss Abstract — Where block (selective mining unit) grade distributions can be determined, the effect of average random errors of block grade estimates on metal recovery can be evaluated quantitatively. That is, for a given estimation error and cutoff grade, it is possible to calculate the quantity of metal that is lost as a result of misclassifying ore blocks as waste, as well as the dilution that ensues from misclassifying waste blocks as ore. Example calculations using a computer program GAINLOSS and realistic block grade distribution parameters for both a porphyry-type deposit and an epithermal gold deposit illustrate some fundamental relations that are important in quality control of estimation and in reconciliations concerning a comparison of ore estimates with production. Where the cutoff grade is on the lower tail of the grade distribution, metal arising from dilution can be much less than metal lost through misclassifying ore as waste. Hence, average grade of milled material could possibly be higher than expected (estimated) and tonnes milled will be smaller than estimated. Where the cutoff grade is on the higher tail of the grade distribution, tonnes arising from dilution will be greater than tonnes lost by misclassifying ore as waste. Thus, tonnage mined will be greater than estimated and the average grade milled will be less than estimated.
Relative Kriging Errors — A Basis for Mineral Resource Classification Abstract — During geostatistical estimation of block grades, the kriging process produces a measure of error, the kriging variance or the kriging standard deviation. Estimation of the block error depends on the semi-variogram model for a deposit, which reflects fundamental characteristics of a deposit such as (1) nugget effect, (2) range of influence of grades, (3) different local spreads of data as a function of average grade (proportional effect), (4) nested structures, and (5) underlying anisotropies in the data; this model may be affected by sampling or assaying limitations, however. Because the kriging error incorporates so many features of both the deposit and data to be used for estimation, it may offer a substantial improvement on block classification over traditional procedures such as data density. Practice indicates that the relative kriging standard deviation (RKSD) is particularly useful for block classification in measured, indicated and inferred categories. Plots of RKSD in plan and section also can be used to demonstrate where extra drilling and sampling would be most advantageous for upgrading the class of some blocks. Moreover, the use of grade and RKSD filters can show where material near cut-off grade is poorly defined, indicating sampling target areas to improve block classification in the vicinity of the ore-waste boundary. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Sampling Quality Control Abstract — Traditionally, samples collected for mineral deposit evaluation have been viewed without explicit reference to reliability, with the illusion that a true value is attainable from a few samples and verifications. For exploration, mineral deposit estimation and production quality control the following definition is proposed: “a sample is a small quantity of material relative to the geological mass it represents, collected according to a systematic procedure, of measurable reliability, from which the grade/quality of the mass which it represents may be estimated, based upon appropriate protocols. This paper will concentrate on the actual rock sampling process. Too often, sample size has been, and is still viewed as a matter of convenience, leaving out representivity considerations, despite the importance of samples on project estimation. Linear samples (chips, channels, drill), panel samples, broken rock or mining samples and very large samples are considered. Collection procedures and quality control protocols to improve the representivity of non-mechanical samples are proposed. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Practical Quality Control Procedures in Mineral Inventory Estimation Abstract—Grass roots exploration has an emphasis on good precision at low (sub-economic) concentrations of an element, in order to identify “anomalies” which may lead to drilling targets. Although it is wise to have well-defined quality controls in place during early stage sampling, the control procedures at this stage tend to be rudimentary. When a deposit warrants detailed delineation, the need for accurate geological characterization and assaying of ore-grade rock must be supported by appropriate quality control procedures. As a project returns more promising results, and the likelihood of the project warranting a pre-feasibility study increases, it is time to tighten quality assurance requirements and quality control protocols. Delays in instituting adequate quality control and verification procedures may lead to costly remedial actions that can also delay completion of the prefeasibility or feasibility study. Sometimes, as a project matures, the quality control and quality assurance aspects fail to keep pace with the changing nature of the work: an increasing emphasis on precise and accurate assaying of ore-grade rock. A resource model is like a house of cards. The foundation of the house is the geological observations, the sampling methods and the geological interpretations performed upon those samples. Upon the sampling, which includes all the sub-sampling steps of sample preparation, rest the assay results. The quality of the assays can be no better than the quality of the sampling. Good assaying technique will preserve all biases and imprecisions introduced during sampling and sample preparation; it cannot remove them. If the sub-samples and/or assays are bad and must be redone, all the succeeding levels of the house of cards must also be rebuilt, or at least patched up. From geological observations, a geological interpretation is built, the quality of which is critical to the construction of an acceptable resource model. Geological elements are difficult to assess, and are not discussed here; they are dependent upon the expertise of the geologists involved. Geological knowledge contributes essential quality control elements to resource/reserve determinations (Sinclair and Postolski, 1999; Postolski and Sinclair, 1999). This paper consists of five sections: (1) overview of quality control protocols, (2) maintaining quality control of databases, (3) quality control of drill sampling, (4) optimizing crushing and grinding requirements, and (5) quality control of assay data acquisition. ©1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Gold Deposits: Establishing Sampling Protocols Abstract — Large differences in gold content between rock fragments or small volumes of unbroken rock, commonly referred to as the nugget effect, are related to sample and subsample weights, crushing and pulverizing sizes, and density, shape and size distribution of gold grains. Gy’s sampling theory, which relates gold grain characteristics to sample weight, fragment size, and error, provides a method of estimating a sampling constant that quantifies deposit characteristics that contribute to the nugget effect. Sampling control tests provide methods for determining the sampling constant. Sampling control charts, comprising nomographs that relate sample weight, error and particle size, use the sampling constant to optimize sample weights and comminution sizes, and to minimize the variability introduced by incorrect or inadequate sampling and sub-sampling procedures. The sampling constant is useful in classifying ores into arbitrary categories according to expected sampling difficulties. Spatial variations in the sampling constant can be used to aid in defining ore types for modeling geological domains, which should have unique sampling protocols. Examples that illustrate the relationship between the sampling constant and expected sampling problems, and the spatial variation of the sampling constant, are given for various deposits. Case histories of sampling programs are presented. Quality control procedures consist of monitoring sample contamination amd accuracy and precision of analytical results. Accuracy, precision and contamination are monitored by including standards, duplicates and blanks into batches of samples being analyzed. Analytical results of standards and blanks are plotted on a batch-and-time basis with control lines at plus or minus two/three standard deviations as confidence limits of the accepted round-robin value. Examples are given that illustrate a laboratory system in statistical control and the various types of problems encountered when interpreting quality control data. These include sample transcription errors, degradation, contamination, sampling errors, detection limit problems, instrumental drift, lack of statistical control, laboratory bias, procedural problems and data tampering. Where bias is negligible, precision, as a function of concentration, can be obtained from duplicates using the Thompson-Howarth precision algorithm, which also allows calculation of the practical detection limit. Examples are given that illustrate variations in precision, with grain size, for different types of duplicates, as well as mineralogical changes and sampling errors. © 1999
NUGGET: PC Software to Calculate Parameters for Samples and Elements Abstract — Reproducible analyses of representative samples for elements affected by the ‘nugget effect’ is vital in mineral exploration and reserve estimation. Unfortunately, a priori knowledge of what size of sample is representative from a mineral deposit or its dispersion train is commonly unavailable. Use of the simple ‘equant grain model’ and the NUGGET computer program facilitates determination of the sampling parameters that will produce appropriate samples for chemical analysis. Based on Poisson statistics, NUGGET can be used to determine: (1) the ‘effective grain size’ of nuggets in a suite of samples, (2) the level of representativity (precision) that samples with specific nugget grain sizes will exhibit, and (3) the sample size required to obtain a specific level of sample representativity. The program determines these sampling parameters for any element in any mineral, including solid solution minerals (e.g., Au, electrum, Pt-Fe alloy, diamond), and allows assumption of a variety of grain shapes (e.g., ellipsoids, cylinders, parallelepipeds, etc.). Furthermore, it outputs the effective number of nuggets expected in a sample of given size and the percentile confidence bounds on any element concentration affected by the nugget effect. Results from the software allow determination of effective sampling and analysis strategies that minimize the nugget effect in geochemical analysis/assaying used in mineral exploration and reserve estimation. This will not only improve confidence in the resulting exploration results or reserve estimate, but will facilitate estimation of the error associated with any subsequent interpretation or reserve figure. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Gold Analysis — Fire Assaying and Alternative Methods Abstract — This paper describes fire assaying and ‘high tech’ alternatives for gold analysis, including advantages and disadvantages of each method. These ‘high tech’ methods include INAA (instrumental neutron activation), aqua regia digestion/AA (atomic absorption), GFAA (graphite furnace-atomic absorption) or ICP/MS (inductively coupled plasma emission mass spectrometry) and a combination of cyanidation with AA, GFAA or ICP/MS methods. Fire assay remains the stalwart among analytical methods for gold but, even with its multiple analytical finishes, is not fool-proof for recovering 100% of the gold present. Consumers of assays should not blindly trust the assay results without consideration of quality control data. Laboratories can and do make mistakes. Some of these can be easily discovered if you do your own due diligence.
Error Variance Information from Paired Data: Applications to Sampling Theory Abstract — A method to extract certain types of error variance information from paired data is presented, which constitutes an important tool for the calibration of Gy’s formula for variance predictions in the sampling of broken ores. The research summarized here complements publications by others on geochemical precision. The model and method proposed for treating duplicate data provide a practical means of deriving separate estimates of the purely analytical and aliquot sampling variances, from a unique set of duplicate assays, and, hence, proposes a new avenue for estimating effective mineral grain size. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Evaluation of Errors in Paired Analytical Data by a Linear Model Abstract — A simple linear model for interpreting duplicate analytical data for a range of values is described. The conceptual model can be quantified using a reduced major axis model rather than the inappropriate traditional least squares approach. The reduced major axis parameters (slope, intercept) and associated errors provide a quantitative basis for: (1) defining bias, and (2) comparing results within laboratories, between laboratories and between sampling/analytical methods. Application of the linear model must be preceded by extraction of obvious outliers or small groups of values that have an inordinately large impact on values of the statistical parameters defining the model. In addition, consideration must be directed to the presence of more than one population of sampling error, as in the case of multiple styles of mineralization being sampled. © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved.
Optimizing the Operational Strategy of a Mine-metallurgy Abstract — This paper deals with industrial complexes such as: (1) a mine producing metal-bearing ore and a furnace(s)/converter(s) where the ore is melted into metal, either directly, or after a mineralurgical concentration; and (2) quarries producing the raw materials required for the manufacturing of cement and the kilns to which they are fed. Each mine or quarry operation results from the exploitation of a mineral deposit. This deposit is never homogeneous. The raw materials which are extracted from the mine/quarry can never be safely fed to a “process” such as a cement kiln or a metal smelter, because the devices involved lack the flexibility required to absorb a very inhomogeneous feed. Furnaces and kilns are known to be very sensitive, sometimes dangerously so, with regard to deviations from a certain ideal feed composition. The purpose of this paper is to present the conditions required to optimize the operation of such a complex, so as to maximize the production, the quality of the product, as well as the profit generated. Two key operations are involved: sampling (to know accurately the materials being dealt with) and bed-blending (to achieve the desired degree of homogeneity). The theories of sampling and bed-blending have been developed by the author and presented in various books (Gy, 1992, 1998). © 1999 Canadian Institute of Mining, Metallurgy and Petroleum. All rights reserved. Last updated: |
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