brendt.wohlberg.net

Brendt Wohlberg and Daniel M. Tartakovsky, "Delineation of Geological Facies from Poorly Differentiated Data", *Advances in Water Resources*, vol. 32, doi:10.1016/j.advwatres.2008.10.014, pp. 225-230, 2009

The ability to delineate geologic facies and to estimate
their properties from sparse data is essential for modeling
physical and biochemical processes occurring in the subsurface.
If such data are poorly differentiated, this challenging task is
complicated further by the absence of a clear distinction
between different hydrofacies at locations where data
*are* available. We consider three
alternative approaches for analysis of poorly differentiated
data: a *k*-means clustering algorithm, an
expectation-maximization algorithm, and a minimum-variance
algorithm. Two distinct synthetically generated geological
settings are used to analyze the ability of these algorithms to
assign accurately the membership of such data in a given
geologic facies. On average, the minimum-variance algorithm
provides a more robust performance than its two counterparts,
and when combined with a nearest-neighbor algorithm, it also
yields the most accurate reconstruction of the boundaries
between the facies.

@article{wohlberg-2009-delineation,

author = {Brendt Wohlberg and Daniel M. Tartakovsky},

title = {Delineation of Geological Facies from Poorly Differentiated Data},

year = {2009},

urlpdf = {http://brendt.wohlberg.net/publications/pdf/wohlberg-2009-delineation.pdf},

journal = {Advances in Water Resources},

volume = {32},

doi = {10.1016/j.advwatres.2008.10.014},

pages = {225-230}

}