Collocated Cokriging Based on Merged Secondary Attributes

被引:22
作者
Babak, Olena [1 ]
Deutsch, Clayton V. [1 ]
机构
[1] Univ Alberta, Dept Civil & Environm Engn, Ctr Computat Geostat, Edmonton, AB T6G 2W2, Canada
关键词
Collocated cokriging; Markov model; Multiple secondary data; Super secondary variable; Multivariate Gaussian model;
D O I
10.1007/s11004-008-9192-2
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
There exist many secondary data that must be considered in in reservoir characterization for resource assessment and performance forecasting. These include multiple seismic attributes, geological trends and structural controls. It is essential that all secondary data be accounted for with the precision warranted by that data type. Cokriging is the standard technique in geostatistics to account for multiple data types. The most common variant of cokriging in petroleum geostatistics is collocated cokriging. Implementations of collocated cokriging are often limited to a single secondary variable. Practitioners often choose the most correlated or most relevant secondary variable. Improved models would be constructed if multiple variables were accounted for simultaneously. This paper presents a novel approach to (1) merge all secondary data into a single super secondary variable, then (2) implement collocated cokriging with the single variable. The preprocessing step is straightforward and no major changes are required in the standard implementation of collocated cokriging. The theoretical validity of this approach is proven, that is, the results are proven to be identical to a "full" approach using all multiple secondary variables simultaneously.
引用
收藏
页码:921 / 926
页数:6
相关论文
共 9 条
[1]   JOINT SIMULATION OF MULTIPLE-VARIABLES WITH A MARKOV-TYPE COREGIONALIZATION MODEL [J].
ALMEIDA, AS ;
JOURNEL, AG .
MATHEMATICAL GEOLOGY, 1994, 26 (05) :565-588
[2]   An intrinsic model of coregionalization that solves variance inflation in collocated cokriging [J].
Babak, Olena ;
Deutsch, Clayton V. .
COMPUTERS & GEOSCIENCES, 2009, 35 (03) :603-614
[3]  
Deutsch C., 1998, GSLIB GEOSTATISTICAL
[4]  
Goovaerts P, 1997, Geostatistics for Natural Resources Evaluation. Applied geostatistics series
[5]   Conditioning geostatistical operations to nonlinear volume averages [J].
Journel, AG .
MATHEMATICAL GEOLOGY, 1999, 31 (08) :931-953
[6]  
Myers D.E., 1982, Matrix Formulation of Co-Kriging, V14, P249
[7]   ESTIMATION OF LINEAR-COMBINATIONS AND CO-KRIGING [J].
MYERS, DE .
JOURNAL OF THE INTERNATIONAL ASSOCIATION FOR MATHEMATICAL GEOLOGY, 1983, 15 (05) :633-637
[8]   Sequential kriging and cokriging:: Two powerful geostatistical approaches [J].
Vargas-Guzmán, JA ;
Yeh, TCJ .
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 1999, 13 (06) :416-435
[9]  
XU W, 1992, P 67 ANN TECHN C EXH