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140122 ||| eng |
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|a 9789401197144
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| 100 |
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|a Annels, A.E.
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| 245 |
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|a Mineral Deposit Evaluation
|h Elektronische Ressource
|b A practical approach
|c by A.E. Annels
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| 250 |
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|a 1st ed. 1991
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| 260 |
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|a Dordrecht
|b Springer Netherlands
|c 1991, 1991
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| 300 |
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|a XV, 436 p
|b online resource
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|a 2.13 The application of copper-sensitive paints -- 2.14 Grade analysis by fluorescence and spectrometric techniques -- 2.15 Sampling theory -- 2.16 Bulk sampling of gold ores -- 3 Ore-Reserves by ‘Classical Methods’ -- 3.1 Introduction -- 3.2 Classification of reserves and resources -- 3.3 Determination of potentially economic intersections -- 3.4 Mine/deposit reserves -- 3.5 Statistical estimators of grade -- 3.6 Ore-reserves by panel/section methods (underground operations) -- 3.7 Ore reserves by triangulation -- 3.8 Ore reserves by polygons -- 3.9 Ore reserves by block matrices -- 3.10 Contour methods -- 3.11 Inverse distance weighting methods (IDW) -- 3.12 Orebody modelling using IDW methods -- Appendix 3.1 USBM/USGS Classification of Resources and Reserves -- Appendix 3.2 APEO Classification of Reserves -- Appendix 3.3 AIMM/AMIC Classification of Resources andReserves -- Appendix 3.4 Coal Resources and Reserves -- Appendix 3.5 Ore reserve calculation — worked example --
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|a 1 Representation of Mine Data -- 1.1 Introduction -- 1.2 Mine nomenclature -- 1.3 Subdivision of orebodies -- 1.4 Mine sections -- 1.5 Mine plans -- 1.6 Vertical longitudinal projections -- 1.7 Structure contour plans -- 1.8 Connolly diagrams -- 1.9 Dip contour maps -- 1.10 Structural unrolling — Palinspastic maps -- 1.11 2D and 3D block models -- 1.12 3D orebody projections -- 1.13 Histograms and cumulative frequency plots -- 1.14 Rose diagrams -- 1.15 Stereographic projections -- 1.16 Computer software -- 2 Mine Sampling -- 2.1 Introduction -- 2.2 Characterization of mineral deposits for sampling purposes -- 2.3 Grade elevation -- 2.4 Possible locations for underground sampling -- 2.5 Channel sampling -- 2.6 Chip sampling -- 2.7 Grab sampling -- 2.8 Percussion/blast-hole sampling -- 2.9 Diamond drill sampling -- 2.10 Prospect sampling -- 2.11 Continuous sampling for open-pit operations -- 2.12 Sampling of unconsolidated surficial deposits --
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|a 8.6 Case history — Boulby Potash Mine, Cleveland, UK -- 8.7 Case history — exploration and evaluation of a glacial sand and gravel deposit (P. Brewer and P. Morse — Tarmac Roadstone, Northwest Limited) -- 8.8 Case history — limestone aggregates — The Tytherington Limestone Quarries, ARC Ltd -- 8.9 Cement — Cement Quality Limestones at Los Cedros, Venezuela (Blue Circle Industries PLC) -- 8.10 Case history — Navan Zn-Pb Mine, Eire (Tara Mines Ltd)
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|a Appendix 4.5 Extension variance graphs and tables for the spherical scheme -- 5 Design and Evaluation of Open-Pit Operations -- 5.1 Introduction -- 5.2 Design of open-pit operations -- 5.3 Evaluation of open-pit operations -- 5.4 Economic optimization of pit designs -- 6 Financing and Financial Evaluation of Mining Projects -- 6.1 Introduction -- 6.2 Financial aspects unique to mining projects -- 6.3 Capitalization of mining projects -- 6.4 Financial model of a mining project -- 6.5 Financial evaluation techniques -- 7 Grade Control -- 7.1 Introduction -- 7.2 Open-pit operations -- 7.3 Underground operations -- 8 Ore-Evaluation Case Histories -- 8.1 Introduction -- 8.2 Case history — White Pine Copper Mine, Michigan, USA -- 8.3 Casehistory — Evaluation of the J-M Pt-Pd Reef, Stillwater, Montana -- 8.4 Case history — East Ore Zone, Teck-Corona Gold Mine, Hemlo Canada -- 8.5 Case history — opencast coal mining in South Wales (R. MacCallum — British Coal) --
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|a Appendix 3.6 Program listing for SGORE -- 4 Geostatistical Ore-Reserve Estimation -- 4.1 Introduction -- 4.2 The application of geostatistics -- 4.3 The theory of regionalized variables -- 4.4 Regularization and orebody subdivision -- 4.5 Production of the semi-variogram -- 4.6 Semi-variogram models -- 4.7 Semi-variogram phenomena in the spherical scheme -- 4.8 Model fitting in the spherical scheme -- 4.9 1D regularization (spherical scheme) -- 4.10 Block reserve estimates by kriging -- 4.11 Global reserve evaluation by kriging -- 4.12 Grade—tonnage curve -- 4.13 Kriging variances and ore-reserve classification -- 4.14 Extension variances in the spherical scheme -- 4.15 Volume—variance relationship -- 4.16 Indicator kriging (IK) -- Appendix 4.1 Determination of confidence limits for log-transformed data -- Appendix 4.2 Worked example — de Wijsian scheme -- Appendix 4.3 Mathematical basis of point kriging -- Appendix 4.4 Mathematical basis of block kriging --
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| 653 |
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|a Humanities and Social Sciences
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| 653 |
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|a Humanities
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| 653 |
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|a Social sciences
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 028 |
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|a 10.1007/978-94-011-9714-4
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| 856 |
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|u https://doi.org/10.1007/978-94-011-9714-4?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 001.3
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|a 300
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| 520 |
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|a Although aspects of mineral deposit evaluation advantages and disadvantages of each technique are covered in such texts as McKinstry (1948), so that a judgement can be made as to their Peters (1978), Reedman (1979) and Barnes applicability to a particular deposit and the min (1980), no widely available in-depth treatment of ing method proposed or used. Too often, a lack the subject has been presented. It is thus the of this expertise results in the ore-reserve calcula intention of the present book to produce a text tion being undertaken at head-office or, indeed, by the survey department on the mine, and being which is suitable for both undergraduate and treated as a 'number crunching' or geometric postgraduate students of mining geology and exercise divorced from geology. It is essential mining engineering and which, at the same time, that mine ore-reserves are calculated at the mine is of use to those already following a professional by those geologists who are most closely associ career in the mining industry. An attempt has ated with the local geology and who are thus best been made to present the material in such a way able to influence and/or constrain the calculation
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