Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/36890
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Plurigau: a computer program for simulating spatial facies using the truncated plurigaussian method
Author: Dowd, P.
Pardo-Iguzquiza, E.
Xu, C.
Citation: Computers and Geosciences, 2003; 29(2):123-141
Publisher: Pergamon-Elsevier Science Ltd
Issue Date: 2003
ISSN: 0098-3004
Statement of
Responsibility: 
P. A. Dowd, E. Pardo-Igúzquiza and C. Xu
Abstract: Truncated plurigaussian simulation is a useful method for simulating spatial categorical variables, such as facies, in a geological context. The method is an extension of the truncated Gaussian method that retains the main advantages of the latter (mainly that it produces permissible sets of indicator semi-variograms and cross-semi-variograms) but overcomes its limitations (the truncated Gaussian method only reproduces sequentially ranked categories). The method is based on the truncation of two Gaussian random functions that may, or may not, be correlated. PLURIGAU is an ANSI Fortran-77 computer program for performing conditional or unconditional truncated plurigaussian simulations of spatial categories. The number of facies, spatial relations between the facies, proportions of each facies, indicator semi-variograms and indicator cross-semi-variograms must be known or estimated from experimental data. The program calculates the four thresholds for each of the facies (two for each of the Gaussian random functions) and the covariance models for the two Gaussian random functions. The simulation of the Gaussian random functions may be done using any of the methods available. Conditioning has been implemented by a simple acceptance–rejection technique embedded within sequential Gaussian simulation algorithm. A case study is provided so that the implementation of the programs can be checked and the results are discussed.
Keywords: Geostatistics
Categorical variable
Indicator semi-variogram
Indicator cross-semi-variogram
Gaussian random field
Sequential Gaussian simulation
DOI: 10.1016/S0098-3004(02)00070-5
Description (link): http://www.sciencedirect.com/science/journal/00983004
Published version: http://dx.doi.org/10.1016/s0098-3004(02)00070-5
Appears in Collections:Aurora harvest 6
Civil and Environmental Engineering publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.