Quantitative analysis of mineral and energy resources
Author(s)
Bibliographic Information
Quantitative analysis of mineral and energy resources
(NATO ASI series, Series C . Mathematical and physical sciences ; no. 223)
D. Reidel Pub. Co
Available at 4 libraries
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  Iwate
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  Niigata
  Toyama
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  Fukui
  Yamanashi
  Nagano
  Gifu
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  Aichi
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  Kyoto
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  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
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  United Kingdom
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Note
"Proceedings of the NATO Advanced Study Institute on Statistical Treatments for Estimation of Mineral and Energy Resources, Il Ciocco, (Lucca) Italy, June 22-July 4, 1986"--T.p. verso
Includes bibliographies and index
Description and Table of Contents
Description
This volume contains the edited papers prepared by lecturers and participants of the NATO Advanced Study Institute on "Statistical Treatments for Estimation of Mineral and Energy Resources" held at II Ciocco (Lucca), Italy, June 22 - July 4, 1986. During the past twenty years, tremendous efforts have been made to acquire quantitative geoscience information from ore deposits, geochemical, geophys ical and remotely-sensed measurements. In October 1981, a two-day symposium on "Quantitative Resource Evaluation" and a three-day workshop on "Interactive Systems for Multivariate Analysis and Image Processing for Resource Evaluation" were held in Ottawa, jointly sponsored by the Geological Survey of Canada, the International Association for Mathematical Geology, and the International Geological Correlation Programme. Thirty scientists from different countries in Europe and North America were invited to form a forum for the discussion of quantitative methods for mineral and energy resource assessment. Since then, not only a multitude of research projects directed toward quantitative analysis in the Earth Sciences, but also recent advances in hardware and software technology, such as high-resolution graphics, data-base management systems and statistical packages on mini and micro-computers, made it possible to study large geoscience data sets. In addition, methods of image analysis have been utilized to capture data in digital form and to supply a variety of tools for charaterizing natural phenomena.
Table of Contents
1. Integration of Data for Resource Evaluation.- Application of recent developments of regression analysis in regional mineral resource evaluation.- Poisson regression analysis and its application.- Measurement, sampling and interpretation.- Levels of information and probability mapping.- Review of geomathematical applications for mineral resources evaluation in China.- 2. Statistical Analysis of Geochemical Data.- New approaches to the recognition of anomalies in exploration geochemistry.- Univariate patterns in the design of multivariate analysis techniques for geochemical data evaluation.- Application of robust statistics in the analysis of geochemical data.- 3. Statistical Mehtods for Oil and Gas Resource Evaluation.- U.S. Geological Survey assessment methodology for estimation of undiscovered petroleum resources in play analysis of the Artic National Wildlife Refuge.- Statistical evaluation of petroleum deposits before discovery.- On assessing dry probabilities in offshore oil and gas exploration: an application of Bayes's theorem.- Statistical analysis of oil and gas discovery data.- 4. Image Processing in Earth Sciences.- Automated integration of mineral resource data by image processing and artificial intelligence.- Principles of mathematical morphology.- The use of geological image analysis in remote sensing and seismic attribute integration for resource assessment.- Statistical image processing.- 5. Statistical Analysis of Spatial Data.- Spatial analysis of patterns of land-based and ocean-floor ore deposits.- Point processes for the earth sciences.- 6. Geostatistics.- An unconventional approach to geostatistical estimation.- Case studies on modelling complex sulphide orebodies for ore reserve estimation using geostatistical methods.- A Bayesian approach to surface estimation.- Conditional simulation of indicator data. Case study of a multi-seam coal deposit.- Factorial kriging as a method to include spatial structure into classification. A case study on a sulphide orebody.- Geostatistical techniques for interpreting multivariate spatial information.- 7. Other Statisitcal Methodologies for Geoscience Data.- The shape of Lloydminster oil and gas deposit attribute data.- Confidence bands for the distribution and quantile functions for truncated and randomly censored data.- Geostatistical crustal abundance resource models.- 8. Artificial Intelligence in Earth Sciences.- The usage of Artificial intelligence in remote sensing: a review of applications and current research.- GEOVALUATOR, an expert system for resource appraisal: a demonstration prototype for kaolin in Georgia, U.S.A.- GEMS: a microcomputer-based expert system for digital image data.- On the understanding of geological cross-sections by expert systems.- 9. Other Contributed Papers.- Examples of spatial analysis and management in the geographical and conformal projection domains.- A classification procedure for exploitable reserves.- Drainage and divide networks derived from high-fidelity digital terrain models.- An algebraic model for data structure and manipulation as a design basis for integrated geoscience processing systems.- Case study on application of qualitative data analysis techniques to an uranium mineralization.- A shell for microcomputer exploration software used in developing countries.- Optimal exploration strategies: the synthesis of resource assessments and operations research.- Advantages and limitations of discovery process modeling: the case of the Northern West Siberian gas plays.- Some aspects of multivariate analysis.- Workshop Reports.- Current problems and future developments in multivariate analysis.- Current problems and future developments in oil and gas resource modeling and forecasting.- Current problems and future developments in spatial statistics and image processing.- Current problems and future developments in mineral and energy resource expert system development.- Current problems and future developments in the use of microcomputers.
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