The simulation of the proportional effect for ore reserve analysis

✍ Scribed by V. Rudenno; M. Richardson

• Book ID: 103895765
• Publisher: Elsevier Science
• Year: 1985
• Tongue: English
• Weight: 500 KB
• Volume: 27
• Category: Article
• ISSN: 0378-4754
• DOI: 10.1016/0378-4754(85)90034-5

✦ Synopsis

SLJMY Geostatistical techniques are used today to obtain the best linear unbiased estimate for block parameter values in mineral deposits. For mineral deposits with sample data that is lognormally distributed the proportional effect is often observed where there is a linear relationship between the variance and squared mean for subsets of the sample population.

Semivariogram models are computed to describe the spatial correlation amongst the sample data. The proportional effect increases the difficulty in observing the underlying semivariogram model.

Relative semivariograms are suggested as better alternatives with emphasis on one particular approach. Conditional stilation was used to verify the relationship between observed results and theory for both the proportional effect and the relative semivariograms. It is suggested that care should be take in determining the slope of the proportional effect and how and when the relative semivariograms should be used in ore reserve evaluation.