Improved spatial modeling by merging multiple secondary data for intrinsic collocated cokriging

Abstract

There often exist many secondary data that must be considered in geostatistical reservoir modeling. These include multiple seismic attributes, geological trends and structural controls. It is essential that all secondary data are accounted for when estimating a primary variable (e.g., porosity or water saturation) with the precision warranted by that secondary data type. Characterizing the distribution of primary and secondary variables requires multivariate geostatistical techniques. Collocated cokriging is a common technique in geostatistics to account for multiple data types. This technique, however, has a longstanding problem with variance inflation that leads to problems in histogram reproduction. This paper, analyses an alternative method to collocated cokriging. This method, referred to as intrinsic collocated cokriging (ICCK), is equally simple, but ensures histogram reproduction. To improve practical implementation of ICCK in the case of multiple secondary data a novel merged secondary variable approach is developed in this paper. This approach is aimed at merging all secondary data into a single variable, then implementing ICCK with that single variable. It is shown that the proposed technique yields the same results as would be obtained using all multiple secondary variables simultaneously.