Research Progress of Oilfield Development Index Prediction Based on Artificial Neural Networks

نویسندگان

چکیده

Accurately predicting oilfield development indicators (such as oil production, liquid current formation pressure, water cut, production rate, recovery cost, profit, etc.) is to realize the rational and scientific of oilfields, which an important basis ensure stable oilfield. Due existing index prediction methods being difficult accurately reflect complex nonlinear problem in field process, using artificial neural network, can predict with function infinitely close any non-linear function, will be most ideal method at present. This article summarizes four commonly used networks: BP radial generalized regression wavelet mainly introduces their network structure, types, calculation process results. Four kinds networks are optimized through various intelligent algorithms, principle essence optimization analyzed. Furthermore, advantages disadvantages summarized compared. Finally, based on application other fields problems, a future direction proposed serve reference guide for research accurate indicators.

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ژورنال

عنوان ژورنال: Energies

سال: 2021

ISSN: ['1996-1073']

DOI: https://doi.org/10.3390/en14185844