2016_EJRNL_PP_PENGYU_GAO_1.pdf
Terbatas  Suharsiyah
» Gedung UPT Perpustakaan
Terbatas  Suharsiyah
» Gedung UPT Perpustakaan
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 multifactors 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.