Implementation of the elemental library stratified sampling technique on the GUI-based Monte Carlo library least squares (MCLLS) approach for EDXRF analysis

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• 作者：Fusheng Li^a ; ^{fusheng.li@bakerhughes.com} ; Robin P. Gardner^b
• 关键词：X-ray fluorescence (XRF) ; Elemental analysis ; Geochemical logging ; Detector response function ; Library least squares method ; Elemental stratified sampling
• 刊名：Applied Radiation and Isotopes
• 出版年：2012
• 期刊代码：6_09698043
• 类别：ce
• 出版时间：July, 2012
• 卷：70
• 期：7
• 页码：1243-1249
• 文件大小：459 K

摘要

The Monte Carlo-based Energy Dispersive X-ray Fluorescence (MCXRF) elemental analyzer approach can be used to accurately calculate elemental weight fractions in rock formations or metal alloys, by least-squares regression of the measured X-ray spectrum with computer-generated elemental library spectra. The analog sampling scheme in a Monte Carlo simulation cannot generate satisfactory results for trace elements due to their low sampling probability. A stratified sampling variance-reduction technique is proposed and implemented to enable each element in the measured sample to have equal opportunity of being sampled with adjusted weights. Essentially, all computed elemental libraries have good statistical precision and improve the accuracy of the elemental analysis results.