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Titlebook: Geostatistical Case Studies; G. Matheron,M. Armstrong Book 1987 Springer Science+Business Media Dordrecht 1987 Kriging.Statistica.gas.hist

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书目名称Geostatistical Case Studies
编辑G. Matheron,M. Armstrong
视频video
丛书名称Quantitative Geology and Geostatistics
图书封面Titlebook: Geostatistical Case Studies;  G. Matheron,M. Armstrong Book 1987 Springer Science+Business Media Dordrecht 1987 Kriging.Statistica.gas.hist
描述It is now nearly 25 years since the first textbook on geostatistics ("Traitj de gjostatistique appliquje" by G. Matheron) appeared in print in 1962. In that time geostatis­ tics has grown from an arcane theory regarded with scepticism by statisticians and miners alike, to a reputable scientific disci­ pline which is routinely used in the geosciences. In the mining industry, in particularly, comparisons between predicted reserve estimates and actual production figures have proved its worth. Few now doubt its usefulness as a statistical tool in the earth sciences. Over the past quarter of a century, many geostatistical case studies have been published but the vast majority of these are routine applications of kriging. Our objective with this volume is to present a series of innovative applications of geostatistics. These range from a careful variographic analysis on uranium data, through detailed studies on geologically complex deposits right up to the latest nonlinear methods applied to deposits with highly skew data distributions. Applications of new techniques such as the external drift method for combining well data with seismic information have also been included. Throughout the
出版日期Book 1987
关键词Kriging; Statistica; gas; history; modelling; production; reservoir; seismic
版次1
doihttps://doi.org/10.1007/978-94-009-3383-5
isbn_softcover978-94-010-8018-7
isbn_ebook978-94-009-3383-5Series ISSN 0924-1973 Series E-ISSN 2215-1834
issn_series 0924-1973
copyrightSpringer Science+Business Media Dordrecht 1987
The information of publication is updating

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https://doi.org/10.1007/978-981-13-1525-1dd universality conditions, but this is not appropriate when estimating the distribution of block grades inside a panel. In this case the estimated panel grade can be used to condition the block grade distribution.
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Book 1987n that time geostatis­ tics has grown from an arcane theory regarded with scepticism by statisticians and miners alike, to a reputable scientific disci­ pline which is routinely used in the geosciences. In the mining industry, in particularly, comparisons between predicted reserve estimates and actu
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