کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
852724 909413 2016 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fluvial facies reservoir productivity prediction method based on principal component analysis and artificial neural network
ترجمه فارسی عنوان
روش پیش بینی وری مخزن Fluvial facies بر اساس تجزیه و تحلیل مولفه های اصلی و شبکه عصبی مصنوعی
کلمات کلیدی
پیش بینی بهره وری؛ تجزیه و تحلیل مولفه اصلی؛ شبکه های عصبی مصنوعی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی (عمومی)
چکیده انگلیسی

It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Petroleum - Volume 2, Issue 1, March 2016, Pages 49–53
نویسندگان
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