Journal
MATHEMATICAL GEOSCIENCES
Volume 41, Issue 8, Pages 921-926Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11004-008-9192-2
Keywords
Collocated cokriging; Markov model; Multiple secondary data; Super secondary variable; Multivariate Gaussian model
Funding
- Alberta Ingenuity Foundation
- University of Alberta
- Centre for Computational Geostatistics
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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.
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