کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4526434 1323836 2009 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Delineation of geological facies from poorly differentiated data
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
پیش نمایش صفحه اول مقاله
Delineation of geological facies from poorly differentiated data
چکیده انگلیسی
The ability to delineate geologic facies and to estimate their properties from sparse data is essential for modeling physical and biochemical processes occurring in the subsurface. If such data are poorly differentiated, this challenging task is complicated further by the absence of a clear distinction between different hydrofacies at locations where data are available. We consider three alternative approaches for analysis of poorly differentiated data: a k-means clustering algorithm, an expectation-maximization algorithm, and a minimum-variance algorithm. Two distinct synthetically generated geological settings are used to analyze the ability of these algorithms to assign accurately the membership of such data in a given geologic facies. On average, the minimum-variance algorithm provides a more robust performance than its two counterparts, and when combined with a nearest neighbor algorithm, it also yields the most accurate reconstruction of the boundaries between the facies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Water Resources - Volume 32, Issue 2, February 2009, Pages 225-230
نویسندگان
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