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Chapter from:
AAPG Memoir 71 : Reservoir Characterization-Recent Advances
Edited by Richard A. Schatzinger and John F. Jordan
Copyright
1999 by The American Association of
Petroleum Geologists. All rights reserved.
Memoir 71, Chapter 27: Nonparametric Transformations for Data Correlation and Integration:
From Theory to Practice , by Akhil Datta-Gupta, Guoping Xue, and Sang Heon Lee , Pages 381
- 396
Chapter 27
Nonparametric Transformations for Data Correlation and
Integration: From Theory to Practice
Akhil Datta-Gupta
Guoping Xue
Sang Heon Lee
Department of Petroleum Engineering
Texas A&M University
College Station, Texas, U.S.A.
ABSTRACT
The purpose of this paper is two-fold. First, we introduce the use of nonparametric
transformations for correlating petrophysical data during reservoir characterization. Such
transformations are completely data driven and do not require an a priori functional
relationship between response and predictor variables, which is the case with traditional
multiple regression. The transformations are very general, computationally efficient, and
can easily handle mixed data types; for example, continuous variables such as porosity,
and permeability, and categorical variables such as rock type and lithofacies. The power
of the nonparametric transformation techniques for data correlation has been illustrated
through synthetic and field examples. Second, we use these transformations to propose a
two-stage approach for data integration during heterogeneity characterization. The
principal advantages of our approach over traditional cokriging or cosimulation methods
are: (1) it does not require a linear relationship between primary and secondary data, (2)
it exploits the secondary information to its full potential by maximizing the correlation
between the primary and secondary data, (3) it can be easily applied to cases where
several types of secondary or soft data are involved, and (4) it significantly reduces
variance function calculations and thus greatly facilitates non-Gaussian cosimulation. We
demonstrate the data integration procedure using synthetic and field examples. The field
example involves estimation of pore-footage distribution using well data and multiple
seismic attributes.