Localized kriging parameters optimization using local uncertainty

Abstract

ABSTRACT Estimates of natural phenomena with spatial correlation, i.e. stationary domains, are more precise and accurate when performed using geostatistical techniques (e.g. kriging). The kriging estimates require the definition of the spatial continuity model and a search strategy. Many techniques, such as unfolding and dynamic anisotropy, try to give some improvement in the estimates, considering the variations of the distributions in the geological bodies, however, the definition of the search strategy in the other parameters is unique. This study presents an alternative to this, called Localized Kriging Parameters optimization (LKPO). LKPO considers the best local kriging parameters settings (block by block) through the local uncertainly (simulations). To illustrate this methodology, a synthetic dataset is presented, and the results are compared with the methodologies currently available in the geostatistical literature. Validation checks show a significant improvement in precision and accuracy on the estimates when using local kriging parameters.