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بین المللی علوم (منتشر نمی شود)
مقاله 4، دوره 3، شماره 0 - شماره پیاپی 1365، مهر 1381 اصل مقاله (245.82 K)
نویسندگان
M. Seddigh Arabani؛ M. Nabi-Bidhendi^*
عنوان مقاله [English]
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چکیده [English]
The objective of this study is a modeling in artificial neural networks (ANN) and its generalization to predict reliable porosity values from log data obtained from three wells in Khangiran gas field located in north-east of Iran. We used a back-propagation ANN method (BP-ANN) to predict porosity. The ANN for porosity is a simple three-layer network which uses sonic, density and resistivity logs for input. Porosity predictions were then compared with log porosity which had been derived from density and neutron logs. The results confirmed the capability of using ANN.
کلیدواژه‌ها [English]
Artificial Neural Network, Khangiran, Mozduran, Porosity, wireline logs

آمار تعداد مشاهده مقاله: 1,080 تعداد دریافت فایل اصل مقاله: 1,628

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