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Karl J. Ellefsen

Publications and source records attributed to Karl J. Ellefsen.

2 recordsLinked to original sources

Effect of mineral deposit data on predictions from the three-part approach to quantitative mineral resource assessment—A study of 16 previous U.S. Geological Survey assessments

The three-part approach to quantitative mineral resource assessment requires information about the properties of undiscovered mineral deposits in an assessment area. These properties are unknown, so the properties of discovered mineral deposits of the same mineral deposit type are used instead. In the three-part approach, these discovered mineral deposits come from around the world, and their properties constitute the pooled data for that mineral deposit type. Alternatively, these discovered mineral deposits could come from the assessment area, and their properties constitute the tract data for that mineral deposit type. Tract data may be more representative of the undiscovered mineral deposits in the assessment area than the pooled data. The goal of this study was to determine whether resource predictions using pooled data are equivalent to resource predictions using tract data. To this end, 16 previous U.S Geological Survey assessments were studied. For each assessment, resources were predicted for one undiscovered mineral deposit in the assessment area. One set of predictions used pooled data, and another used tract data. The two sets of predictions were compared with an equivalence test, using the six assessment statistics that are commonly reported for mineral resource assessments. Practical equivalence is the condition that two corresponding assessment statistics are within a factor of 1.5 of one another. For each of 2 assessments, all 6 assessment statistics were practically equivalent. For both assessments, the assessment statistics from the pooled data, relative to the corresponding assessment statistics from the tract data, ranged from 1.30 times smaller to 1.03 times larger. For each of 14 assessments, 1 or more of the 6 assessment statistics were not practically equivalent. The assessment statistics from the pooled data, relative to the corresponding assessment statistics from the tract data, ranged from 26.6 times smaller to 5.53 times larger. The use of pooled data has been a standard procedure in the three-part approach since at least 1986. The 16 assessments in this study are not a representative sample of those prior assessments that used pooled data. So, it is inappropriate to use the study results to infer whether pooled data affected the resource predictions for those prior assessments.

Scientific Investigations Report

Bayesian mapping of regionally grouped, sparse, univariate earth science data

Some earth science data are naturally grouped by region, and it is often desirable to map these data by region. However, if there are only a few samples within each region, then the map should be smoothed in an appropriate way to mitigate the problems that arise from having only a few samples. A smoothing algorithm based on a Bayesian hierarchical model is developed and presented in this report. This algorithm has several features that make it especially suitable for mapping earth science data: it can account for measurements that are censored, it can process multiple datasets with different measurement errors and different censoring thresholds, and it can calculate the uncertainty in any statistic that is mapped. The algorithm is demonstrated by mapping gold concentrations that are measured in streambed sediments in the Taylor Mountains quadrangle in southwestern Alaska.

Alaska