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SUPRPUMP: An Interactive Program for Well Test Analysis and Design (1992)

Bohling, Geoffrey C. ; McElwee, Carl D.

Oxford, UK : Blackwell Publishing Ltd

Ground water 30 (1992), S. 0

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ISSN: 1745-6584

Source: Blackwell Publishing Journal Backfiles 1879-2005

Topics: Energy, Environment Protection, Nuclear Power Engineering , Geosciences

Notes: Abstract. We have developed a program which aids in the design and analysis of pumping tests and slug tests. In design mode, the program emphasizes calculation and plotting of the sensitivities of drawdown (or head) to well function parameters. In analysis mode, the program can analyze a given set of experimental data. For pumping tests, the program allows multiple observation wells and multiple variable-rate pumping wells. The program is written in a modular fashion, allowing easy addition of well functions to the currently existing library. An example based on a hypothetical pumping test illustrates the utility of sensitivity analysis for well test design.

Type of Medium: Electronic Resource

URL: http://dx.doi.org/10.1111/j.1745-6584.1992.tb01799.x

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Singularity and Nonnormality in the Classification of Compositional Data (1998)

Bohling, Geoffrey C. ; Davis, John C. ; Olea, Ricardo A. ; [et al.]

Springer

Mathematical geology 30 (1998), S. 5-20

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ISSN: 1573-8868

Keywords: regionalization ; compositions ; pseudo-inverses ; logratio transforms

Source: Springer Online Journal Archives 1860-2000

Topics: Geosciences , Mathematics

Notes: Abstract Geologists may want to classify compositional data and express the classification as a map. Regionalized classification is a tool that can be used for this purpose, but it incorporates discriminant analysis, which requires the computation and inversion of a covariance matrix. Covariance matrices of compositional data always will be singular (noninvertible) because of the unit-sum constraint. Fortunately, discriminant analyses can be calculated using a pseudo-inverse of the singular covariance matrix; this is done automatically by some statistical packages such as SAS. Granulometric data from the Darss Sill region of the Baltic Sea is used to explore how the pseudo-inversion procedure influences discriminant analysis results, comparing the algorithm used by SAS to the more conventional Moore–Penrose algorithm. Logratio transforms have been recommended to overcome problems associated with analysis of compositional data, including singularity. A regionalized classification of the Darss Sill data after logratio transformation is different only slightly from one based on raw granulometric data, suggesting that closure problems do not influence severely regionalized classification of compositional data.