Iterative disjoint cluster and discriminant function processing

Details Iterative disjoint cluster and discriminant function processing Iterative disjoint cluster and discriminant function processing

1988-02-16

1990-06-26

Atkinson, Charles E.

Boots, shoes, and leggings

324323, G01V 1100

Patent

active

049377477

ABSTRACT:
A set of representative subpopulations of a dataset such as a set of depth related formation log responses is selected by (a) classifying the dataset into n=a disjoint clusters; (b) determining discriminant function for the thus produced n=a disjoint clusters; (c) generating a measure respresentative of agreement/disagreement betweeen the classification generated by cluster analysis in step (a) and the classification generated by discriminant analysis in step (b); (d) repeating steps a-c for other numbers n=a, b, c, . . . ; and (e) selecting the set n=k where k is a, b, c, . . . , where the measure shows best agreement.

REFERENCES:
patent: 4646240 (1987-02-01), Serra et al.
patent: 4648268 (1987-03-01), Grosjean
Gill, "Application of a Statistical Method to Reservoir Evaluation and Digitized Log Analysis", AAPG Bulletin, vol. 54, No. 5, (1970), pp. 719-729.
Hempkins, "Discriminant and Cluster Analysis as Statistical Aids in Stratigraphic Correlation", AAPG Bulletin, vol. 66, No. 5, (1982), p. 581.
Busch, "Determination of Lithology From Well Logs by Statistical Analysis", SPE, 14301, presented Sep. 22-25, 1985.
Baldwin and Morrow, "Identifying Subsurface facies from User-Directed Computer Processing of Log and Other Data," Association Round Table, p. 462.
Anderbert, Cluster Analysis for Applications, Chapter 7, "Nonhierarchical Clustering Methods," (1973).
Davis, Statistics and Data Analysis in Geology, pp. 442-456, "Discriminant Functions".
SAS.RTM. USERS GUIDE: Statistics, Version V Edition, Chapter 16, "The DISCRIM Procedure," and Chapter 18, The FASTCLUS Procedure, (1985).

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