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Quantitative assessment of mineral resources with an application to petroleum geology

Nonrenewable Resources

By:
, , and
DOI: 10.1007/BF01782114

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Abstract

The probability of occurrence of natural resources, such as petroleum deposits, can be assessed by a combination of multivariate statistical and geostatistical techniques. The area of study is partitioned into regions that are as homogeneous as possible internally while simultaneously as distinct as possible. Fisher's discriminant criterion is used to select geological variables that best distinguish productive from nonproductive localities, based on a sample of previously drilled exploratory wells. On the basis of these geological variables, each wildcat well is assigned to the production class (dry or producer in the two-class case) for which the Mahalanobis' distance from the observation to the class centroid is a minimum. Universal kriging is used to interpolate values of the Mahalanobis' distances to all locations not yet drilled. The probability that an undrilled locality belongs to the productive class can be found, using the kriging estimation variances to assess the probability of misclassification. Finally, Bayes' relationship can be used to determine the probability that an undrilled location will be a discovery, regardless of the production class in which it is placed. The method is illustrated with a study of oil prospects in the Lansing/Kansas City interval of western Kansas, using geological variables derived from well logs. ?? 1992 Oxford University Press.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Quantitative assessment of mineral resources with an application to petroleum geology
Series title:
Nonrenewable Resources
DOI:
10.1007/BF01782114
Volume
1
Issue:
1
Year Published:
1992
Language:
English
Publisher location:
Kluwer Academic Publishers
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Nonrenewable Resources
First page:
74
Last page:
84