J. G. De Geoffroy, T. K. Wignall

Statistical Models for Optimizing Mineral Exploration (eBook, PDF)

• Format: PDF

Produktbeschreibung

After the spectacular successes of the 1960's and 1970's, the mineral exploration business is at a crossroads, facing uncertain t:imes in the decades ahead. This situation requires a re-thinking of the philosophy guiding mineral exploration if it is to emulate its recent performance. The ma:i. n argument of a previous volume titled "Designing Opt:lmal Strategies for Mineral Exploration", published in 1985 by Plenum Publishing Corporation of New York, is that a possible answer to the challenge facing mineral explorationists lies in the philosophy of opt:irn1zation. This new approach should help exploration staff make the best achievable use of the sophisticated and costly technology which is presently available for the detection of ore deposits. The main emphasis of the present volume is placed on the mathematical and computational aspects of the opt:irn1zation of mineral exploration. The seven chapters making up the ma:i. n body of the book are devoted to the description and application of various types of computerized geomathematical models which underpin the optimization of the mineral exploration sequence. The topics covered include: (a) the opt:lmal selection of ore deposit types and regions of search, as well as prospecting areas within the regions (Chapters 2, 3, 4, 6), (b) the designing of airborne and ground field programs for the opt:lmal coverage of prospecting areas (Chapters 2, 3, 4), (c) delineation and evaluation of exploration targets within prospecting areas by means of opt:irn1zed models (Chapter 5).

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Produktdetails

• Verlag: Springer New York
• Seitenzahl: 444
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461318613
• Artikelnr.: 44183272

Inhaltsangabe

1 Application of computerized geomathematical models to the optimization of exploration programs.- 1.1. General statement: optimization of the mineral exploration sequence.- 1.2. Types of geomathematical models used for optimizing mineral exploration.- 1.3. Construction of a data base for the optimized search for six types of ore deposits in five continents.- 2 Deterministic, heuristic and univariate stochastic models used for optimizing mineral exploration.- 2.1. Foreword: types of models used in the optimized ore deposit search.- 2.2. Deterministic models.- 2.3. Heuristic models.- 2.4. Univariate stochastic models.- 2.5. Modelling of economic & geometric parameters of ore deposits.- 2.6. Modelling of occurrence parameters of ore deposits.- Exercises.- 3 Statistical pooling of regions to assist the optimization of world-wide ore search programs.- 3.1. General statement: rationale of statistical pooling of regions.- 3.2. Testing of population commonality.- 3.3. Sequential testing of population commonality.- 3.4. Application of sequential testing procedure to assist the world-wide search for six types of ore deposits.- 3.5. Application of sequential testing to assist continent-wide search programs for six types of ore deposits.- Exercises.- 4 Probabilistic models for the optimal detection of ore deposits by airborne and ground exploration programs.- 4.1. General statement: detection of ore deposits based on Geometric Probability.- 4.2. Detection of randomly oriented ore deposits by airborne surveys on grids of various designs.- 4.3. Detection of randomly oriented ore deposits by ground surveys or vertical drilling on square grids.- 4.4. Detection of oriented ore deposits by airborne and ground surveys and drilling programs. Application of Dynamic Programming.- 4.5. Optimization of airborne and ground field surveys and drilling programs based on detection probability models.- 4.6. Selection of ore deposit types and regions of search based upon the detectability criterion.- 4.7. Optimal selection of region-ore deposit types based on the discounted payoff criterion.- Exercises.- 5 Application of the General Linear Model and Operations Research models to the optimization of field exploration and development planning.- 5.1. Theoretical background for the GLM.- 5.2. Application of regression analysis to various mineral exploration problems.- 5.3. Application of trend factor and residual trend factor analyses to field exploration programs.- 5.4. Application of Operations Research models to development planning.- Exercises.- 6 Multivariate Bayesian classification models: Application to the optimal selection of prospecting areas and exploration targets.- 6.1. General statement.- 6.2. Optimal selection of prospecting areas and exploration targets based on control data.- 6.3. Optimal selection of exploration targets without control data.- Exercises.- 7 The Expert computerized system for optimizing mineral exploration.- Appendices.- A.1. List of names of ore deposits included in data base.- A.3. SEQPOOL computer programs.- A.4. OPTGRID computer programs.- A.5. FACTOR-TREND computer programs.- A.6. Linear Programming dual simplex computer program.- A.7. CLASSIFICATION computer programs.- A.8. Data lists for exercises.- A.9. Measurement conversion table and statistical tables.- A.10. Answers to selected exercises.