کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10272003 | 461157 | 2014 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evaluation of chemical composition of waters associated with petroleum production using Kohonen neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
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چکیده انگلیسی
The analysis with Kohonen neural networks allowed assessing the chemical profile of each production zone, and identifying the formation of clusters related to the individual oil wells, as well as patterns related to seasonality. Production Zone 1 revealed the presence of two distinct sample populations associated to the different oil wells from which samples originated as from two different reservoirs. Production Zone 2 presented a homogeneous cluster of samples from the same oil well, and Production Zone 3 revealed five samples clusters constituted by samples from five different oil wells from the same reservoir. It was also possible to identify samples with anomalous behavior and characterize them according to the contents of the variables involved.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuel - Volume 117, Part A, 30 January 2014, Pages 381-390
Journal: Fuel - Volume 117, Part A, 30 January 2014, Pages 381-390
نویسندگان
Fabiana A.L. Ribeiro, Francisca F. Rosário, Maria C.M. Bezerra, Rita de Cássia C. Wagner, André L.M. Bastos, Vera L.A. Melo, Ronei J. Poppi,