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By A. Unal

Coal resource characterization usually calls for estimating more than one variable over a block or node simultaneously. Within the realm of geostatistics, each variable has been evaluated independently from the others assuming a lack of significant correlation. Research conducted with coal seams, however, has shown that the variables of immediate interest, such as seam thickness, ash, sulfur content, and density depict some correlation schemes in distinct zones, if not throughout the entire area. The above findings have two immediate consequences : (1) correlation analyses provide guidelines to determine the geologically distinct zones, and (2) where possible, cokriging should be used instead of kriging. This will maximize data utilization decreasing the frequently criticized high estimation errors. The cokriging formulation will also provide more accurate estimates for under sampled variables using better-sampled ones. This is a common case with coal with regard to the non-cored reconnaissance drill holes for which only very few variables were recorded. A case study illustrates the improvements that may be obtained by taking advantage of the intervariable correlations.

Jan 1, 1986

By P. Diehl

The increasing public interest in a useful framework for an assessment and classification of mineral resources (1) is documented by the recently published international classification scheme of the United Nations (1979) and the revision of the classification system of USBM/USGS (2) (1980). Moreover, various classification systems are currently discussed by the mining industry. In spite of major improvements in respect of the concepts, definitions, and taxonomy of ore classification, it has been recognized that the recent practice to classify mineral resources does not create truly reproductible results, i.e. an assessment to the various categories which is free from personal bias or corporate interests. Following are geostatistical methods proposed for a standardization and quantification of various terms in ore classification. After critical review of present practices, we will establish a precise link between the classical terms such as "measured", "indicated", and "inferred" reserves and the geostatistical concept of estimation errors. Moreover, we will demonstrate, how the basic criteria of economic feasibility, geologic assurance and recovery can be taken into account by geostatistics. A specific algorithm will be proposed to block out and to classify reserves according to the degree of geologic assurance. . We will also show computerized methods which perform complete classification procedures, and will also exemplify them with typical case studies.

Jan 1, 1982

By G. Pan

A geostatistical approach is proposed for the design of infill drilling programs. The method consists of the following four major steps: developing geological favorability models, delineating mineralization and ore envelopes, classifying resource potentials, and designing infill drilling patterns. Geological modeling develops the permissible geological zones in which infill drilling is designed. Modeling mineralization and ore envelopes establishes criteria on the potential blocks to be drilled. The blocks that are included within the ore envelopes are considered in the infill drilling. The following four types of resource potentials are used in this analysis: measured, indicated, possible and barren. Blocks in the indicated category are the top targets to be confirmed in infill drilling. Blocks of possible resources may be considered exploration targets. The algorithms involved in the analysis include indicator favorability analysis, indicator kriging and ordinary kriging. A case study on a gold deposit of the Carlin type is presented to demonstrate the methodology. The deposit was originally delineated by a sparse drilling program with about 230ft of average spacing. The infill drilling design, based on the new method, suggests a significant reduction on the number of holes from a regular-grid infill drilling pattern.

Jan 1, 1996

By G. Pan

A geostatistical approach is proposed for the design of infill drilling programs. The method is consisted of three major steps: developing geological favorability models, delineating mineralization and ore envelopes, and classifying reserves or resources. Geological modeling aims at developing favorable geological zones in which drilling is designed. Modeling mineralization and ore envelopes establishes criteria on potential blocks to be drilled. Top target blocks should be those included within ore envelopes. The framework of resource categories includes five types: probable reserves, indicated reserves, indicated resources, possible resources, and barren. Indicated reserves or resources are the top priority to be drilled for the definition of minable reserves. Possible resources may be considered as targets for further exploration. The algorithms involved in the analysis include indicator favorablity analysis, ordinary kriging, and indicator kriging. A case study presented here involves a gold deposit of Carlin type. The deposit was delineated by a sparse drilling program with 230 feet of average spacing. The infill drilling program designed by the new method suggests a significant reduction on the number of holes from a regular-grid infill drilling pattern.

Jan 1, 1995

By Dominigue Francois-Bongarcon

This paper presents a step by step vulgarized review of the applications of geostatistics to the estimation of the mineable, recoverable reserves of the Cinola gold deposit in British Columbia.

Jan 1, 1988

By Y. C. Kim

The results from a retrospective study are described in this gaper in which she past development drilling activities were investigated using geostatistics. The purpose of the study was to determine the amount of savings in drilling cost that could have been realized through the optimal placement of sequential drill holes using geostatistics. Out of 144 DDH's that were in place within the study area, the results showed a possible elimination of 34 DDH's without any reduction on the confidence interval of the global reserve estimates. If the incremental savings from one drilling campaign to the next were considered, however, the amount of percentage savings were even greater. Other interesting results from this study were; 1) tangible demonstration of the importance of a proper geologic delineation within the study zone, and 2) the robustness of the obtained experimental variograms from the rather early stage in development drilling.

Jan 1, 1981

By D. E. Ranta, M. G. Hester

The ore reserve modelling of stratiform uranium deposits to be mined by selective underground mining methods must be done with consideration of the erratic nature of the ore-forming processes that produced the mineralization. Estimation methods that model the uranium grade as a smooth transition between high-grade and low-grade drill hole intercepts tend to greatly overestimate the ore tonnage. Care must be taken to first establish realtistic ore pod geometries and then estimate the grade of the reserve units within the pods.

Jan 1, 1992

By M. G. Hester

The ore reserve modeling of stratiform uranium deposits to be mined by selective underground mining methods must be done with consideration of the erratic nature of the ore forming processes that produced the mineralization. Estimation methods that model the uranium grade as a smooth transition between high grade and low grade drillhole intercepts tend to greatly overestimate the ore tonnage. Care must be taken to first establish realistic ore pod geometries and then estimate the grade of the reserve units within the pods.

Jan 1, 1985

By John S. F. Dunlop

One of the more difficult problems frequently facing geologists and mining engineers is that of estimating the ore reserves of mineral deposits. Cost conscious mining operations invariably require an accurate knowledge of tonnage and grade for both short and long term planning. A case study is presented, showing how a classical frequency distribution was fitted to a population of drillhole assays. Using these results, a grade- tonnage curve is derived using the Lasky expressions, and the results discussed. A geostatistical analysis is then presented. First, variograms are drawn, models fitted to them and analyses made of drift and anisotropy. Second, simple block kriging is carried out and the results plotted on large 1000 scale plans, suitable for overlay with routine .mine plans. Kriging results are verified using two independent techniques: random kriging on a regular grid and inverse distance weighting. Finally an attempt is made to optimize the drilling grid, and to fully tabulate the total computer running costs for the work described.

Jan 1, 1979

By Kalyan Saikia

An integrated statistical-geostatistical modelling of gold exploration data of Gurahar Pahar prospect of Mahakoshal greenstone belt in Central India has been attempted. Statistical modelling of gold accumulation and width reveal a positively skewed 2-parameter lognormal distribution fit with an estimate of mean gold as 0.84 gram/tonne. Geostatistical modelling provided a spherical semi-variogram function fit with mean kriged estimate and mean kriging variance of gold as 0.76 gram/tonne and 0.23 (gram/tonne)2 -respectively. Ore inventory and grade-tonnage relationships for a selected part provided an estimate of 3,36,000 tomes of ore with an average gold of 0.76 gram/tonne at 0.5 gram/tonne cutoff grade.

Jan 1, 2002

By Indranil Roy

Gua supergene enriched iron ore deposit from Jharkhand, India has been geostatistically modeled. Population modeling shows a negatively skewed 3-parameter log-normal fit for Fe and positively skewed 3-parameter log-normal fit for Al2O3 and SO2. Semi-variographic studies for Fe indicate spherical function fit using point kriging cross-validation technique with Co=4.06(%)2, C5.11 (%)2, Co+C=9.1 7(%)2 and 'a'=348m. Kriging with 50mx50mx 10m block size at 740mRL led to a global mean kriged estimate of 61.98% and kriging variance of 4.04(%)2 for Fe with central 90% geostatistical confidence limits at 61.39% and 62.24% for that level. This led to an ore inventory at 740mRL as 7.29 million tonnes of ore.

Jan 1, 2002

By Hassan Madani, A. Malek Mohammadi

Dorreh barite mine located in the central part of Iran is one of the largest barite mines, in the country. The mine is subdivided into three blocks, which are called block 1,2,3 according the barite quality. In the central part of each block, a heavily concentrated grid of exploratory drill holes have been drilled and the reserves of area was calculated based on these holes, some years ago. It was decided to compute the reserve of the area by geostatistical methods, in the form of an M.Sc. project. In order to study the area, three regionalized variables including density, thickness and density-thickness (accumulation) was studied and the spherical variograms were fitted to these variables. These models were evaluated by cross-validation method. The optimized block size was chosen in order to compute the reserves by kriging method. The reserves of explored parts of each block of mine was calculated and the results were extended to the whole area of the blocks. The reserve of the explored parts and the total reserve of the area were calculated to be 96,000t and 1,670,000t respectively.

Jan 1, 1996

By Mehmet Guney

[The Atlantis-II-Deep is a hydrothermal mineralization located along the median valley of the Red Sea at a water depth of about 2200 m. Extensive exploration of the metal-rich brine deep revealed a potentially mineable deposit on economic interest consisting of oxides, silicates and sulphides with considerable concentrations of zinc, copper, cadmium and silver. Geostatistics was applied to assess the most likely in-situ vague of the metal potential for economical exploitation. Semi-variograms were constructed to characterize the structure of the regionalized distribution of the geological parameters. Volume grades and thicknesses were determined by the kriging technique, avoiding systematically biased high or low grades, and then block .tonnages were computed. The estimation variances, distribution of errors and histograms of observed and kriged values in each grid Mock were also produced.]

Jan 1, 1983

By Th. Petropulos

The Zn-Ag-Pb mineralization zone near Molai (Greece) was explored by more, than 60 drillholes. Promising results led to the decision of additional drillholes in order to confirm the expected spatial extension of the deposit. A multiobjective approach is described which optimizes the location of a set of 5 additional drillholes. The decision is based on estimation errors for grade, thickness and depth of the main ore bearing layer, with respect to cut-off values for grade and thickness. The linear combination of these variables defines a favorability index which is used for mapping optimal drillhole locations. The map shows several clusters of favorable cells. A declustrering algorithm is used to select a representative cell for drilling in each cluster.

Jan 1, 1989

By Jaime Guzman

Mineral exploration decision problems involve the economic evaluation of upgraded geological information and the costs of obtaining it. This paper presents a valuation theory of risky projects applicable to the analysis of exploration investments. The valuation model is predicated on the Capital Asset Pricing Model (CAPM) from financial economics; its parameters can be objectively measured from publicly available information. Geostatistics is used to derive simplified random cash flow models which incorporate the impact of improved deposit knowledge in terms of reduced estimation variance. The application of the theory is illustrated by means of hypothetical exploration optimization examples.

Jan 1, 1986

By M. G. Hester

The inadequacy of traditional geostatistical methods for estimating some precious metals deposits has become apparent in the last few years. New methods or estimation such as Indicator, Probability and Multigaussian Kriging are difficult to understand and apply. Case studies using a new method of variogram calculation proposed by Srivastava show the method valuable for variogram estimation in precious metal deposits. Some simple, sometimes unorthodox. estimation methods that have proved useful in Some situations are presented.

Jan 1, 1990

By Jacques Deraisme

Geostatistics has been applied in many mining feasibility studies throughout the world during the last decade. Recently geostatistics has begun to be applied to the field of mining processes by attempting to aid in the definition of the best mining policy. For a feasibility study the grade-tonnage relationships give a reasonable order of magnitude estimate of the ore reserves within the deposit. But the reserves that will actually be recovered, will vary depending upon the mining methods and the technical means used. The profit earning capacity of the mining project is determined by a great many factors, such as for instance: accessibility of reserves to extracting machines, the haulage distance between the mine and the mill, the variability of produced ore (tonnage and grades) which could necessitate stockpiles or blending areas?

Jan 1, 1979

By Dominique Francois-Bongarcon

The world mining industry is facing a severe recession. Thus, it is time to recall the value of geostatistical methods which were formerly developed as a money-saving and productivity-increasing tool. The situation has worsened, but the techniques of geostatistics have dramatically changed. Up to millions of dollars can be saved during exploration with simple use of variograms; then, during reserves estimation with kriging methods; and finally, with the parameterization of reserves, when evaluating a project and optimizing its global mining parameters.

Jan 1, 1983

Geostatistics is well known as a tool for ore reserves calculations at the exploration stage. The goal of this paper is to show geoscatistics can also contribute to productivity gains, allow better selection of the mining methods and better control of the grades during production. The first two examples show how geostatistics can provide sophisticated models, using conditional simulations and the use of them for simulations or optimizations of mining processes. A third example will show how to use geostatistics for short term planning in a large polymetallic vein type mine.

Jan 1, 1983

By Francis Martino

Just as coal producing mines are faced with various handicaps which control the quantity of coal produced and sold, the subsequent user of that product is faced with parameters that impact the optimum utilization of coal. Traditionally, the industry focused on the quantity of mineable coal in a reserve. The mine planning development was primarily concerned with two important criteria: (1) safety and (2) the productive efficiency in a quest to produce the lowest cost coal.

Jan 1, 1982