کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8865842 1620864 2018 73 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Machine learning strategies for classification and prediction of alteration facies: Examples from the Rosemont Cu-Mo-Ag skarn deposit, SE Tucson Arizona
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات زمین شناسی اقتصادی
پیش نمایش صفحه اول مقاله
Machine learning strategies for classification and prediction of alteration facies: Examples from the Rosemont Cu-Mo-Ag skarn deposit, SE Tucson Arizona
چکیده انگلیسی
The best RF model is used to predict Alteration Facies on 33,000 drill core samples in which multi-element geochemistry is available but the skarn alteration is uncertain due to the lack of XRD-mineralogy. The predicted alteration shows that the Ep skarn facies occurs above the economic mineralization within Mesozoic siliciclastic and volcanic rocks of the Upper plate. The GrtPxWoVes skarn and SrpAm skarn occur within Paleozoic carbonate rocks of the Lower Plate and West Block. Accordingly, the Ep skarn facies can be used to target blind Cu-Mo-Ag rich porphyry-skarn mineralization in areas where the Paleozoic carbonate rocks are concealed under the Mesozoic siliciclastic and volcanic rocks.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Geochemical Exploration - Volume 194, November 2018, Pages 167-188
نویسندگان
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