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Are you familiar with Kriging Neighborhood Analysis (KNA)?
Are you familiar with Kriging Neighborhood Analysis (KNA)?
This method is used to optimise and understand the impact of search ellipsoid parameters. The neighbourhood parameters can significantly affect the estimation of ordinary kriging and the simulation output. One common mistake is to oversmooth (or undersmooth) grade, leading to incorrect decision-making in the mining process.
It is not unusual to see reports overlooking the analysis of neighbourhood parameters, when it shouldn’t.
Kriging Neighborhood Analysis is typically used to define the shape of the search ellipsoid, minimum/maximum number of samples and number of angular sectors. KNA usually focuses on the following parameters:
- the slope of regression of the real unknown grade on the estimated grade,
- the kriging variance,
- the proportion and distribution of negative weights,
- and the weight of the mean obtained by simple kriging.
Would you like to incorporate KNA into your resource estimation process? DeepLime can assist you in setting up a personalised framework tailored to your deposits and specific requirements.
