Abstract

A genetic- support vector regression algorithm for oil field development and production prediction

Author(s): Guo Dongfeng

Accurate prediction of oil production is very important to help the company make a reasonable plan and avoid blind investment and achieve sustainable development. The selection of the appropriate parameters of support vector regression algorithm is very important for the forecasting performance of support vector regression algorithm. This study employs genetic algorithm to select the appropriate parameter of support vector regression algorithm.Thus, this paper presents genetic- support vector regression algorithm for oil field development and production prediction. The comparison of the oil production forecasting error among genetic-support vector regression algorithm shows that the oil production forecasting error of genetic-support vector regression algorithm is small than support vector regression algorithm and BP neural network.


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