The bias caused by the String Effect in ordinary Kriging: risks and solutions

ABSTRACT

Kriging relies on the assumption that the study area is within an infinite domain. In practice, Kriging is performed in a finite domain, generally defined by geology, and a string of samples along a drillhole is commonly truncated inside this domain. In the Kriging system, the string-end samples receive more weight as they are less screened. This feature is referred to as the ‘String Effect’ and becomes a concern in non-stationary domains in which the end and central samples are systematically different, such as (i) domains with grade enrichment or diminution towards the centre, or (ii) end samples are partially contaminated with material from adjacent domains due to sampling methods. Three methods available in the literature and one novel approach (Kriging with Adjusted Declustering [KAD]) are applied to continuous and categorical variables in three case studies. The KAD results in a significant improvement in the results of all case study models.

KEYWORDS:

• Geostatistics
• Kriging with string of data
• screening effect
• String Effect
• Kriging in a finite domain
• Kriging with variance of measurement error
• mining
• KVME

Disclosure statement

No potential conflict of interest was reported by the author(s).