Petroleum Science >2010,??Issue 3:??379-384 DOI: https://doi.org/10.1007/s12182-010-0081-1
Using a support vector machine method to predict the development indices of very high water cut oilfields Open?Access
文章信息
作者：Zhong Yihua,Zhao Lei,Liu Zhibin,Xu Yao and Li Rong
作者單位：
School of Sciences, Southwest Petroleum University, Chengdu, Sichuan 610500, China;School of Sciences, Southwest Petroleum University, Chengdu, Sichuan 610500, China;School of Sciences, Southwest Petroleum University, Chengdu, Sichuan 610500, China;Sichuan Forestry Cadre School, Chengdu, Sichuan 610066, China;School of Sciences, Southwest Petroleum University, Chengdu, Sichuan 610500, China
投稿時(shí)間：2009-06-23
引用方式：Zhong, Y., Zhao, L., Liu, Z. et al. Pet. Sci. (2010) 7: 379. https://doi.org/10.1007/s12182-010-0081-1
文章摘要
Because the oilfields in eastern China are in the very high water cut development stage,accurate forecast of oilfield development indices is important for exploiting the oilfields efficiently. Regarding the problems of the small number of samples collected for oilfield development indices, a new support vector regression prediction method for development indices is proposed in this paper. This method uses the principle of functional simulation to determine the input-output of a support vector machine prediction system based on historical oilfield development data. It chooses the kernel function of the support vector machine by analyzing time series characteristics of the development index; trains and tests the support vector machine network with historical data to construct the support vector regression prediction model of oilfield development indices; and predicts the development index. The case study shows that the proposed method is feasible, and predicted development indices agree well with the development performance of very high water cut oilfields.
關(guān)鍵詞
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Oilfield development indices, oilfield performance, support vector regression, high water cut, time series